WO2012177607A1 - Translating phrases from one language into another using an order-based set of declarative rules - Google Patents
Translating phrases from one language into another using an order-based set of declarative rules Download PDFInfo
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- WO2012177607A1 WO2012177607A1 PCT/US2012/043100 US2012043100W WO2012177607A1 WO 2012177607 A1 WO2012177607 A1 WO 2012177607A1 US 2012043100 W US2012043100 W US 2012043100W WO 2012177607 A1 WO2012177607 A1 WO 2012177607A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/40—Processing or translation of natural language
- G06F40/55—Rule-based translation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/40—Processing or translation of natural language
- G06F40/55—Rule-based translation
- G06F40/56—Natural language generation
Definitions
- an application or other code is configured to provide audible or other prompts, or other output information, to a user in a language or other symbolic communication system other than a native language of the application or other code
- a mapping between an internal representation of the output information in a native language and a corresponding translated expression of the output information in the target symbolic communication system in which it is to be rendered is required.
- a developer charged with providing the ability to be able to render such information in a selected one of a plurality of target symbolic communication systems, such as one of a plurality of supported spoken languages has been required to understand applicable communication system rules of the target communication systems, such as applicable grammar and other syntactic rules in the case of spoken languages.
- code may be written to match a prompt or other application output to one or more corresponding audio files, which are played in sequence to communicate the output information audibly in the target language, using proper grammar, correct pronunciation and intonation, etc.
- Figure 1 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system.
- Figure 2 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system.
- Figure 3 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system.
- Figure 4 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system.
- Figure 5 is a flow diagram illustrating an embodiment of a process to translate application information into an internal representation usable to communicate the information in a targeted language or other symbolic communication system.
- Figure 6 is a flow diagram illustrating an embodiment of a process to configure a system to translate application information into an internal representation usable to communicate the information in a targeted language or other symbolic communication system.
- Figures 7A and 7B illustrate an example of applying an ordered set of declarative rules to generate an intermediate representation in some embodiments.
- Figures 8A and 8B illustrate an example of applying an ordered set of declarative rules to generate an intermediate representation in some embodiments.
- Figure 9A illustrates examples of rules of transposition and inheritance in some embodiments.
- Figure 9B shows an example that illustrates application of the rules shown in
- Figure 10 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system via a desired medium.
- Figure 1 1 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system via a desired medium.
- Figures 12A and 12B illustrate an example of matching an internal representation to one or more output data files in an embodiment.
- Figures 12C and 12D illustrate an example of matching an internal representation to one or more output data files in an embodiment.
- Figure 13 is a flow diagram illustrating an embodiment of a process to configure a system to communicate information in a target symbolic communication system via a desired medium.
- the invention can be implemented in numerous ways, including as a process; an apparatus; a system; a composition of matter; a computer program product embodied on a computer readable storage medium; and/or a processor, such as a processor configured to execute instructions stored on and/or provided by a memory coupled to the processor.
- these implementations, or any other form that the invention may take, may be referred to as techniques.
- the order of the steps of disclosed processes may be altered within the scope of the invention.
- a component such as a processor or a memory described as being configured to perform a task may be implemented as a general component that is temporarily configured to perform the task at a given time or a specific component that is manufactured to perform the task.
- the term 'processor' refers to one or more devices, circuits, and/or processing cores configured to process data, such as computer program instructions.
- an ordered set of declarative rules is applied to generate a representation that expresses the information in a manner that embodies applicable communication system rules of a target symbolic communication system, such as a spoken language, in which the information is to be rendered as a sensory perceptible output, such as audible spoken words comprising a sentence or phrase that expresses the information.
- a target symbolic communication system such as a spoken language
- audible spoken words comprising a sentence or phrase that expresses the information.
- Applications, mobile devices and system, consumer electronics, and other devices may be configured to provide prompts or other output information to a user.
- Such information may be desired to be communicated in a target symbolic communication system and potentially via a target medium, such as audio output that communicates the information in a target spoken language, are audio or other prompts to be provided to an application and/or system user.
- An application and/or device may be configured to provide the information as output in response to an event or other trigger.
- such information is provided in a machine usable form intelligible in the first instance to a receiving component, such as binary data corresponding to a string of characters according to an encoding scheme.
- a target symbolic communication system such as a spoken human language
- information To be rendered as output in a target symbolic communication system, such as a spoken human language, such information must be mapped to a set of one or more media files, which can be played or otherwise rendered in sequence to communicate the information, for example audibly in a spoken language the user understands.
- an application or system may be configured to provide to a user prompts that reflect information associated with the user's interaction with an application and/or system.
- the NikeTM + iPodTM offerings include products and software that enable a user to configure their iPodTM or iPhoneTM to receive sensor information, for example from a workout machine or a sensor installed in their athletic shoe, and/or GPS or other data from the mobile device, and to use such information to monitor the user's progress in the course of a workout or other activity.
- the user may receive, for example, prompts or other information indicating an amount of time they have been exercising, how far they've run, their pace, calories calculated to have been burned, and prompts reflecting milestones such as the halfway point of a run or a timed activity and/or prompts toward the end of a workout indicating time or distance left to go.
- Figure 1 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system.
- information 102 is received by a translator 104 configured to apply an ordered set of declarative rules 106 to generate an internal representation 108 of the information 102.
- the internal representation 108 embodies applicable rules of a target symbolic communication system, such as a target human language, in which the information 102 is to be communicated.
- the internal representation 108 embodies communication system rules such as those governing the order of words in a sentence or fragment thereof; how grammatical number is expressed, such as plural versus singular; gender of nouns and modifiers thereof; conjugation of verbs; selection from among a plurality of tones that may correspond to a character, syllable, word, or other linguistic unit; etc.
- the internal representation 108 uses words or other linguistic units of a first language to express the information, but in an order and/or joined by connectors, etc. in a manner that reflects one or more syntactic rules of the target language or other communication system.
- the internal representation 108 is provided to a matcher 1 10.
- the matcher 1 The matcher
- the 110 is configured to compare the internal representation 108 and/or portions thereof to filenames of files (or other objects) 1 12 to find one or more "best fit" files.
- the "best fit" files are those that match the largest portion of the information as expressed in internal representation 108.
- the matched files 1 14 are rendered by player 116 to communicate the information as rendered output 118, for example, spoken words in a target language.
- FIG. 2 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system.
- the information to be communicated is that the user has "65 meters to go” (202) before reaching some milestone, such as the end of a run of a desired distance.
- the target symbolic communication system is spoken English
- the internal representation 204 in the example shown uses English words to express the elements comprising the information in a manner that conforms to the semantic and grammatical rules of spoken English, for example, quantity greater than one requires the plural "meters", quantity precedes units, etc.
- the internal representation 204 is provided to matcher 110, which executes a generic (i.e., target language agnostic) matching algorithm to find a set of audio files 206 that best matches the internal representation 204.
- the matched files 206 comprise three audio files (.aif), storing respectively for example audio data created by having a voice actor speak the word "sixty", the word "five", and phrase "meters to go", respectively.
- the player 116 uses the matched audio files to render the information as output, in this case the spoken English phrase "sixty five meters to go".
- a number of output files such as audio files, to which a source word, number, or other linguistic unit is mapped may vary depending on the target language. For example, in English the number “21 " may be mapped in various embodiments to two files (a first to render spoken "twenty” and a second to render spoken "one") or, for example to achieve greater fluency, to a single file (e.g., spoken "twenty one"). In other languages, however, more or fewer files may be required.
- application output such as the number "21” are first parsed to identify informational elements (here the number "21") to which a target language (or language family) associated set of rules are applied to generate an internal representation that embodies syntactic rules of the target language in a manner that enables the generic matcher to find the most correct audio files to be used to express the information, as described more fully below.
- FIG. 3 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system.
- a mobile or other computing device 302 has an application 304 running on it.
- the application 304 may be running in a runtime or other environment provided by an operating system of the device 302.
- the application 304 in this example is configured to receive user input 306, for example via a hard or soft button, touch screen, wired or wireless connected input device, spoken commands, and/or one or more other input devices and/or interfaces.
- the application 304 in this example is configured to receive sensor input 308, for example from an external sensor such as those described above in connection with the NikeTM + iPodTM example or internal sensors and/or other sources of information, such as GPS information.
- the application is configured at least in part by settings 310.
- One such setting for example, may indicate a target language or other symbolic
- translation engine 314 comprises a rule engine and associated logic configured to apply an ordered set of declarative rules 316 to received application information 312 to generate an internal representation 318 of the information 312.
- the internal representation 318 is provided to a file matching logic 320 configured to use a list of filenames of media (or other) files stored in a file store 322 to find one or more files that best match the received internal representation 318.
- the matched files are rendered by media player 324 via an output device driver 326 and output device 328, such as a speaker, ear buds, or other audio output device.
- FIG 4 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system.
- application information that is to be rendered as sensory perceptible output is received (402).
- a structured internal representation of the information is produced (404).
- One or more output files (or other objects) are matched to the structured internal representation (406).
- the matched output files are rendered to produce a sensory perceptible output that communicates the information (408).
- an ordered set of declarative rules is applied to translate an application or other information into a form that enables the information to be communicated, via automated processing and without human intervention, in a target language or other symbolic communication system.
- Figure 5 is a flow diagram illustrating an embodiment of a process to translate application information into an internal representation usable to communicate the information in a targeted language or other symbolic communication system.
- the process of Figure 5 is used to implement 404 of Figure 4.
- application information that is to be communicated is parsed to discern one or more informational elements (502).
- An ordered set of declarative rules is applied to generate based on the informational elements an internal representation that expresses the information to be communicated in a manner that embodies applicable communicate system rules of a target symbolic communication system in which the information is to be communicated (504).
- Figure 6 is a flow diagram illustrating an embodiment of a process to configure a system to translate application information into an internal representation usable to communicate the information in a targeted language or other symbolic communication system.
- an ordered set of declarative rules is received and stored (602).
- the rules in some embodiments are included in a .plist or other file using an appropriate syntax, language, and/or protocol supported by the destination device.
- the rules are constructed and ordered based on communication system rules of a target symbolic communication system with which they are associated.
- a separate rule set may be defined for each of a plurality of target symbolic communication systems.
- rules sets and/or portions thereof may overlap and/or otherwise be shared among rule sets associated with multiple different target communication systems.
- the system may be configured to use the same .plist or portion thereof to apply those rules.
- the rules are constructed to be used to translate application or other output information to generate an internal representation that reflects applicable communication system rules of an associated target communication system in which the information is to be communicated.
- Examples of rules received at (602) include rules of substitution (e.g., replace the number "3" with the word "three" in specified contexts), rules of transposition (e.g., in general move adjective to follow noun when translating from English to Spanish), and rules of inheritance (e.g., in some languages an adjective typically inherits grammatical number and gender from a noun the adjective modifies).
- rules of substitution e.g., replace the number "3" with the word "three” in specified contexts
- rules of transposition e.g., in general move adjective to follow noun when translating from English to Spanish
- rules of inheritance e.g., in some languages an adjective typically inherits grammatical number and gender from a noun the adjective modifies.
- a translation engine is configured to apply the rules, recursively and in order, to generate an internal representation (604).
- Figures 7A and 7B illustrate an example of applying an ordered set of declarative rules to generate an intermediate representation in some embodiments.
- Figure 7A shows a first declarative rule 702 and a second declarative rule 704.
- Rule 702 defines a pattern that if matched results in an indicated value comprising the information and/or an intermediate representation thereof to be replaced by the same value followed by the place value identifier "hundred". In this case, if a non-zero number followed by two digits preceding zero or more sets of three digits before a decimal point is encountered, the number is replaced by the number followed by the place identifier "hundred".
- Rule 704 defines a pattern that if matched results in an indicated value comprising the information and/or an intermediate representation thereof to be replaced by the same value followed by the place value identifier "thousand". Specifically, if a non-zero number followed by a single digit, the place value identifier "hundred” and two more digits immediately before a decimal point is encountered, the number is replaced by the number followed by the place identifier
- place value identifiers such as “hundred” and “thousand” are not inserted as separate segments, as shown in Figures 7A and 7B, but are instead added as post-context tags appended to the number they modify, such as the number "five” or the first occurrence of the number "three” in the example shown in Figures 7A and 7B.
- using the post-context tag approach to represent place value identifiers facilitates rule creation, because simpler and/or more intuitive rules can be defined due to the fact that application of one rule, such as the "hundreds" rule described above, does not affect and have to be anticipated by other rules, such as the "thousands" rule described above.
- Figure 7B shows an example of application of the rules in Figure 7A to the application information "317513" (720).
- Application of rule 702 results in substitutions that yield the intermediate representation 722.
- Application of rule 704 to intermediate representation 722 in turn yields intermediate representation 724.
- the condition (left side as shown) of rule 704 would not have been met if rule 702 had not already been applied.
- the rules in this example have been constructed and ordered to efficiently yield the desired result. Note also that if the rules had been in the opposite order, with rule 704 appear first in the rule set, in a first iteration through the rules rule 704 would not have been triggered.
- the translator or other entity applying translation rules iterates recursively through the rule set until no applicable rule is found.
- rules 702 and 704 were reversed, in the first pass through rule 704 would not have been triggered but rule 702 would have been triggered and enforced.
- rule 704 would have been triggered and applied, yielding the same end result.
- other rules not shown in Figures 7A and 7B have been applied to yield a final internal representation 726, for example, rules to replace the digits "1-7" and "1-3" with the words "seventeen” and "thirteen", respectively.
- Figures 8A and 8B illustrate an example of applying an ordered set of declarative rules to generate an intermediate representation in some embodiments.
- a set of declarative rules 800 includes rules of substitution constructed to translate into Spanish information received originally (or transformed in an intermediate operation into) English.
- the rules shown in Figure 8A may comprise an applicable subset of a broader set of rules, the other members of which are not shown for purposes of simplicity and clarity, and which other rules would not be triggered in the example shown in Figure 8B, for example.
- a series of translations 820 are performed by applying rules 800 in order to an original (or intermediate) representation of the information "the onions" 822.
- the rules 800 are applied sequentially and in order, for each rule substituting the expression on the left side as shown with the replacement expression on the right side, to yield in the end the translated internal representation 824, i.e., the expression "las cebollas", which is how one communicates the concept of a plurality of onions in Spanish.
- the internal representation 824 that is shown as being generated include linguistic elements, specifically words, in the target language.
- the internal representation may comprise words or other linguistic elements in an original language of the application, for example, or some other language other than the target language.
- the internal representation may comprise words or other linguistic elements in an original language of the application, for example, or some other language other than the target language.
- [_definiteArticle_feminine_plural] [onion_feminine_plural]” may be generated in some embodiments, expressing the information and associated meta-information in English but to be matched in some embodiments to filenames in English of audio files comprising data to render the spoken Spanish words "las” (the feminine plural definite article in Spanish) and “cebollas” (the plural of "onions", which is a feminine noun in Spanish).
- use of a common namespace language to express the information to be communicated and associated meta-information, such as communication system rules or meta-information relevant to such rules, for files associated with a plurality of target languages or other communication systems one or more of which may be different from the namespace language facilitates use of a relative simple and target language/system agnostic matcher to identify output files that match the internal representation and can be used to render the information in the target communication system and medium.
- Figure 9A illustrates examples of rules of transposition and inheritance in some embodiments.
- rule 902 provides on the left side as shown that if an adjective immediately preceding a noun that the adjective modifies is encountered, the adjective should be moved to a position immediately following the noun, as is done when translating from English to Spanish for example.
- Rule 904 provides that if a noun that has gender and grammatical number attributes is followed by an adjective that does not (yet) have such attributes, the adjective inherits the attribute values from the noun that precedes it.
- Figure 9B shows an example that illustrates application of the rules shown in
- FIG. 9A in an embodiment.
- a starting representation 920 in English the words “the red onions” results in the example shown in the representation 922 comprising the Spanish words “las cebollas rojas", in which the feminine plural form of the adjective “red” (“rojas") appears following the noun it modifies ("cebollas” or "onions").
- the internal representation is in a common language, such as English, but embodies
- an internal representation of an information to be communicated is received and matched to one or more output data files usable to
- a target symbolic communication system for example, a target spoken language
- a desired medium e.g., audio output
- Figure 10 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system via a desired medium.
- an internal representation that expresses, in a common output file namespace language, information to be communicated in a target language is received (1002).
- the internal representation is used to find by filename one or more output files that best match the internal representation (1004).
- the matched files are rendered to
- Figure 1 1 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system via a desired medium.
- the process of Figure 1 1 is used to implement 1004 of Figure 10.
- a modified "largest match" approach is implemented. Specifically, at each level starting with a top level (i.e., looking for a single file name that matches the entire internal representation), the matcher first looks for a file that is an exact match of the information and meta- information at that level.
- the matcher checks to see if there is a match if one or more elements of meta- information, e.g., one or more meta-information tags, are ignored. For example, files that include complete phrases may not include in their name meta-information such as gender for each or even any words included in the phrase, since such meta- information would not in the case of use of such a file be required to also match correctly corresponding files for definite articles, adjectives, and other modifiers.
- the process starts at a top level (1102) and looks for a match at that level (1 104). If a file matching the entire internal representation is found (1 106), that file is used (1108) and the process ends (11 14).
- Figures 12A and 12B illustrate an example of matching an internal representation to one or more output data files in an embodiment.
- a set of output files 1200 includes audio files 1202, 1204, 1206, 1208, and 1210 as shown.
- the internal representation 1220 is first checked at a top level (entire representation) to seek a match. Since no file named "one_feminine_calorie_to_go" is found, the gender tag "feminine" is ignored temporarily to continue processing at the current level, as shown in modified representation 1222, resulting in a match to file 1202 being found.
- the file name is in English but the audio content when rendered is the corresponding spoken phrase in Spanish "una caloria para terminar".
- Figures 12C and 12D illustrate an example of matching an internal representation to one or more output data files in an embodiment.
- the same output files 1200 as in Figure 12A are matched to the internal representation 1240 of Figure 12D.
- no file name matches the entire top level representation, either with or without the tag
- Figure 13 is a flow diagram illustrating an embodiment of a process to configure a system to communicate information in a target symbolic communication system via a desired medium.
- output files are received and stored (1302). For example, .aif or other audio files recorded using voice actors to speak words and/or phrases in a target spoken language are received in some embodiments.
- a list (or other data structure) of file names of the received files is received or generated (1304).
- a matching logic is configured to use the list of file names to find files that best match a received string or other internal representation of information to be communicated (1306).
- target symbolic communication systems may include, without limitation, translating from an internal representation comprising a string into a displayed written communication in a target font or language, for example using techniques described herein to select font elements to render ligatures comprising two or more adjacent characters properly using a single vector graphic or other file; translating from a string embodying note data into pictures of music notes and/or to render as audible music; and selecting based on an internal string
- representation tile image files usable to represent two or more different types of terrain, such as to show a land region, a body of water, and a properly rendered coast or other border between them, in one of a plurality of target visual themes or scenarios.
- communication such as spoken language
- techniques described herein may be used to communicate information via other media, such as other sensory perceptible output, including without limitation visual display; multi-media displays; haptic technologies, Braille, or other tactile output; or any other sensory perceptible output used to communicate information according to a symbolic communication system.
Abstract
Translating a phrase from one language into another using an order-based set of declarative rules is disclosed. Information to be communicated as sensory perceptible output is received. An ordered set of rules is applied to generate a representation that expresses the information in a manner that embodies applicable communication system rules of a target symbolic communication system in which the information is to be communicated. Output in the target language may be arrived at by speech synthesis, concatenating named audio files to produce grammatical speech.
Description
TRANSLATING PHRASES FROM ONE LANGUAGE INTO ANOTHER
USING AN ORDER-BASED SET OF DECLARATIVE RULES
BACKGROUND OF THE INVENTION
[0001] Typically, when an application or other code is configured to provide audible or other prompts, or other output information, to a user in a language or other symbolic communication system other than a native language of the application or other code, a mapping between an internal representation of the output information in a native language and a corresponding translated expression of the output information in the target symbolic communication system in which it is to be rendered is required. Typically, a developer charged with providing the ability to be able to render such information in a selected one of a plurality of target symbolic communication systems, such as one of a plurality of supported spoken languages, has been required to understand applicable communication system rules of the target communication systems, such as applicable grammar and other syntactic rules in the case of spoken languages. Based on such knowledge, for example, code may be written to match a prompt or other application output to one or more corresponding audio files, which are played in sequence to communicate the output information audibly in the target language, using proper grammar, correct pronunciation and intonation, etc.
BRIEF DESCRIPTION OF THE DRAWINGS
[0002] Various embodiments of the invention are disclosed in the following detailed description and the accompanying drawings.
[0003] Figure 1 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system.
[0004] Figure 2 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system.
[0005] Figure 3 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system.
[0006] Figure 4 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system.
[0007] Figure 5 is a flow diagram illustrating an embodiment of a process to translate application information into an internal representation usable to communicate the information in a targeted language or other symbolic communication system.
[0008] Figure 6 is a flow diagram illustrating an embodiment of a process to configure a system to translate application information into an internal representation usable to communicate the information in a targeted language or other symbolic communication system.
[0009] Figures 7A and 7B illustrate an example of applying an ordered set of declarative rules to generate an intermediate representation in some embodiments.
[0010] Figures 8A and 8B illustrate an example of applying an ordered set of declarative rules to generate an intermediate representation in some embodiments.
[0011] Figure 9A illustrates examples of rules of transposition and inheritance in some embodiments.
[0012] Figure 9B shows an example that illustrates application of the rules shown in
Figure 9A in an embodiment.
[0013] Figure 10 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system via a desired medium.
[0014] Figure 1 1 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system via a desired medium.
[0015] Figures 12A and 12B illustrate an example of matching an internal representation to one or more output data files in an embodiment.
[0016] Figures 12C and 12D illustrate an example of matching an internal representation to one or more output data files in an embodiment.
[0017] Figure 13 is a flow diagram illustrating an embodiment of a process to configure a system to communicate information in a target symbolic communication system via a desired medium.
DETAILED DESCRIPTION
[0018] The invention can be implemented in numerous ways, including as a process; an apparatus; a system; a composition of matter; a computer program product embodied on a computer readable storage medium; and/or a processor, such as a processor configured to execute instructions stored on and/or provided by a memory coupled to the processor. In this specification, these implementations, or any other form that the invention may take, may be referred to as techniques. In general, the order of the steps of disclosed processes may be altered within the scope of the invention. Unless stated otherwise, a component such as a processor or a memory described as being configured to perform a task may be implemented as a general component that is temporarily configured to perform the task at a given time or a specific component that is manufactured to perform the task. As used herein, the term 'processor' refers to one or more devices, circuits, and/or processing cores configured to process data, such as computer program instructions.
[0019] A detailed description of one or more embodiments of the invention is provided below along with accompanying figures that illustrate the principles of the invention. The invention is described in connection with such embodiments, but the invention is not limited to any embodiment. The scope of the invention is limited only by the claims and the invention encompasses numerous alternatives, modifications and equivalents. Numerous specific details are set forth in the following description in order to provide a thorough understanding of the invention. These details are provided for the purpose of example and the invention may be practiced according to the claims without some or all of these specific details. For the purpose of clarity, technical material that is known in the technical fields related to the invention has not been described in detail so that the invention is not unnecessarily obscured.
[0020] Transforming application or other output information into a form that enables the information to be communicated, for example audibly or otherwise, is disclosed.
Application or other information to be provided as output is received. In various embodiments, an ordered set of declarative rules is applied to generate a representation that expresses the information in a manner that embodies applicable communication system rules of a target symbolic communication system, such as a spoken language, in which the information is to be rendered as a sensory perceptible output, such as audible spoken words comprising a sentence or phrase that expresses the information.
[0021] Application Prompts and Other Information to be Communicated
[0022] Applications, mobile devices and system, consumer electronics, and other devices may be configured to provide prompts or other output information to a user. Such information may be desired to be communicated in a target symbolic communication system and potentially via a target medium, such as audio output that communicates the information in a target spoken language, are audio or other prompts to be provided to an application and/or system user. An application and/or device may be configured to provide the information as output in response to an event or other trigger. Typically, such information is provided in a machine usable form intelligible in the first instance to a receiving component, such as binary data corresponding to a string of characters according to an encoding scheme. To be rendered as output in a target symbolic communication system, such as a spoken human language, such information must be mapped to a set of one or more media files, which can be played or otherwise rendered in sequence to communicate the information, for example audibly in a spoken language the user understands.
[0023] For example, an application or system may be configured to provide to a user prompts that reflect information associated with the user's interaction with an application and/or system. The Nike™ + iPod™ offerings, for example, include products and software that enable a user to configure their iPod™ or iPhone™ to receive sensor information, for example from a workout machine or a sensor installed in their athletic shoe, and/or GPS or other data from the mobile device, and to use such information to monitor the user's progress in the course of a workout or other activity. The user may receive, for example, prompts or other information indicating an amount of time they have been exercising, how far they've run, their pace, calories calculated to have been burned, and prompts reflecting milestones such as the halfway point of a run or a timed activity and/or prompts toward the end of a workout indicating time or distance left to go.
[0024] System Overview
[0025] Figure 1 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system. In the example shown, information 102 is received by a translator 104 configured to apply an ordered set of declarative rules 106 to generate an internal representation 108 of the information 102. In some embodiments, the internal representation 108 embodies applicable rules of a target
symbolic communication system, such as a target human language, in which the information 102 is to be communicated. For example, in various embodiments the internal representation 108 embodies communication system rules such as those governing the order of words in a sentence or fragment thereof; how grammatical number is expressed, such as plural versus singular; gender of nouns and modifiers thereof; conjugation of verbs; selection from among a plurality of tones that may correspond to a character, syllable, word, or other linguistic unit; etc.
[0026] In some embodiments, the internal representation 108 uses words or other linguistic units of a first language to express the information, but in an order and/or joined by connectors, etc. in a manner that reflects one or more syntactic rules of the target language or other communication system.
[0027] The internal representation 108 is provided to a matcher 1 10. The matcher
110 is configured to compare the internal representation 108 and/or portions thereof to filenames of files (or other objects) 1 12 to find one or more "best fit" files. In some embodiments, the "best fit" files are those that match the largest portion of the information as expressed in internal representation 108. The matched files 1 14 are rendered by player 116 to communicate the information as rendered output 118, for example, spoken words in a target language.
[0028] Figure 2 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system. In the example shown, the information to be communicated is that the user has "65 meters to go" (202) before reaching some milestone, such as the end of a run of a desired distance. The translator 104 in this example has provided the internal representation 204, in which the information has been parsed into informational elements (quantity = 65, units = meters, significance = "to go") and an ordered set of rules has been applied to the informational elements to generate the internal representation 204 as shown. In this example the target symbolic communication system is spoken English, and the internal representation 204 in the example shown uses English words to express the elements comprising the information in a manner that conforms to the semantic and grammatical rules of spoken English, for example, quantity greater than one requires the plural "meters", quantity precedes units, etc.
[0029] The internal representation 204 is provided to matcher 110, which executes a generic (i.e., target language agnostic) matching algorithm to find a set of audio files 206 that best matches the internal representation 204. In the example shown, the matched files 206 comprise three audio files (.aif), storing respectively for example audio data created by having a voice actor speak the word "sixty", the word "five", and phrase "meters to go", respectively. The player 116 uses the matched audio files to render the information as output, in this case the spoken English phrase "sixty five meters to go".
[0030] In some embodiments, a number of output files, such as audio files, to which a source word, number, or other linguistic unit is mapped may vary depending on the target language. For example, in English the number "21 " may be mapped in various embodiments to two files (a first to render spoken "twenty" and a second to render spoken "one") or, for example to achieve greater fluency, to a single file (e.g., spoken "twenty one"). In other languages, however, more or fewer files may be required. For example, in German, the correct syntax (expressed in English) would be "one and twenty", in Japanese it would be "two ten one", while in Italian it would be a single word in which major parts of the separate words for "twenty" and "one" are compressed into the single word "ventuno". Therefore, in various embodiments application output, such as the number "21" are first parsed to identify informational elements (here the number "21") to which a target language (or language family) associated set of rules are applied to generate an internal representation that embodies syntactic rules of the target language in a manner that enables the generic matcher to find the most correct audio files to be used to express the information, as described more fully below.
[0031] Figure 3 is a block diagram illustrating an embodiment of a system configured to communicate information in a target symbolic communication system. In the example shown, a mobile or other computing device 302 has an application 304 running on it. For example, the application 304 may be running in a runtime or other environment provided by an operating system of the device 302. The application 304 in this example is configured to receive user input 306, for example via a hard or soft button, touch screen, wired or wireless connected input device, spoken commands, and/or one or more other input devices and/or interfaces. The application 304 in this example is configured to receive sensor input 308, for example from an external sensor such as those described above in connection with the Nike™ + iPod™ example or internal sensors and/or other sources of information, such as GPS information. In addition, the application is configured at least in part by settings 310.
One such setting, for example, may indicate a target language or other symbolic
communication system in which application prompts are to be communicated. The application 304 provides prompts (or other information to be communicated) 312 to a translation engine 314. In some embodiments, translation engine 314 comprises a rule engine and associated logic configured to apply an ordered set of declarative rules 316 to received application information 312 to generate an internal representation 318 of the information 312. The internal representation 318 is provided to a file matching logic 320 configured to use a list of filenames of media (or other) files stored in a file store 322 to find one or more files that best match the received internal representation 318. The matched files are rendered by media player 324 via an output device driver 326 and output device 328, such as a speaker, ear buds, or other audio output device.
[0032] Figure 4 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system. In the example shown, application information that is to be rendered as sensory perceptible output is received (402). A structured internal representation of the information is produced (404). One or more output files (or other objects) are matched to the structured internal representation (406). The matched output files are rendered to produce a sensory perceptible output that communicates the information (408).
[0033] Determining What is to be Communicated
[0034] In various embodiments, an ordered set of declarative rules is applied to translate an application or other information into a form that enables the information to be communicated, via automated processing and without human intervention, in a target language or other symbolic communication system.
[0035] Figure 5 is a flow diagram illustrating an embodiment of a process to translate application information into an internal representation usable to communicate the information in a targeted language or other symbolic communication system. In various embodiments, the process of Figure 5 is used to implement 404 of Figure 4. In the example shown, application information that is to be communicated is parsed to discern one or more informational elements (502). An ordered set of declarative rules is applied to generate based on the informational elements an internal representation that expresses the information to be
communicated in a manner that embodies applicable communicate system rules of a target symbolic communication system in which the information is to be communicated (504).
[0036] Figure 6 is a flow diagram illustrating an embodiment of a process to configure a system to translate application information into an internal representation usable to communicate the information in a targeted language or other symbolic communication system. In the example shown, an ordered set of declarative rules is received and stored (602). The rules in some embodiments are included in a .plist or other file using an appropriate syntax, language, and/or protocol supported by the destination device. The rules are constructed and ordered based on communication system rules of a target symbolic communication system with which they are associated. In some embodiments, a separate rule set may be defined for each of a plurality of target symbolic communication systems. In some embodiments, rules sets and/or portions thereof may overlap and/or otherwise be shared among rule sets associated with multiple different target communication systems. For example, for spoken languages that share certain semantic or other rules and/or classes of rule the system may be configured to use the same .plist or portion thereof to apply those rules. The rules are constructed to be used to translate application or other output information to generate an internal representation that reflects applicable communication system rules of an associated target communication system in which the information is to be communicated.
[0037] Examples of rules received at (602) include rules of substitution (e.g., replace the number "3" with the word "three" in specified contexts), rules of transposition (e.g., in general move adjective to follow noun when translating from English to Spanish), and rules of inheritance (e.g., in some languages an adjective typically inherits grammatical number and gender from a noun the adjective modifies).
[0038] A translation engine is configured to apply the rules, recursively and in order, to generate an internal representation (604).
[0039] Figures 7A and 7B illustrate an example of applying an ordered set of declarative rules to generate an intermediate representation in some embodiments. Figure 7A shows a first declarative rule 702 and a second declarative rule 704. Rule 702 defines a pattern that if matched results in an indicated value comprising the information and/or an intermediate representation thereof to be replaced by the same value followed by the place value identifier "hundred". In this case, if a non-zero number followed by two digits
preceding zero or more sets of three digits before a decimal point is encountered, the number is replaced by the number followed by the place identifier "hundred". Rule 704 defines a pattern that if matched results in an indicated value comprising the information and/or an intermediate representation thereof to be replaced by the same value followed by the place value identifier "thousand". Specifically, if a non-zero number followed by a single digit, the place value identifier "hundred" and two more digits immediately before a decimal point is encountered, the number is replaced by the number followed by the place identifier
"thousand".
[0040] In some alternative embodiments, place value identifiers such as "hundred" and "thousand" are not inserted as separate segments, as shown in Figures 7A and 7B, but are instead added as post-context tags appended to the number they modify, such as the number "five" or the first occurrence of the number "three" in the example shown in Figures 7A and 7B. In some embodiments, using the post-context tag approach to represent place value identifiers facilitates rule creation, because simpler and/or more intuitive rules can be defined due to the fact that application of one rule, such as the "hundreds" rule described above, does not affect and have to be anticipated by other rules, such as the "thousands" rule described above.
[0041] Figure 7B shows an example of application of the rules in Figure 7A to the application information "317513" (720). Application of rule 702 results in substitutions that yield the intermediate representation 722. Application of rule 704 to intermediate representation 722 in turn yields intermediate representation 724. In this example, note that the condition (left side as shown) of rule 704 would not have been met if rule 702 had not already been applied. The rules in this example have been constructed and ordered to efficiently yield the desired result. Note also that if the rules had been in the opposite order, with rule 704 appear first in the rule set, in a first iteration through the rules rule 704 would not have been triggered. In some embodiments, the translator or other entity applying translation rules iterates recursively through the rule set until no applicable rule is found. In such an embodiment, if the order of rules 702 and 704 were reversed, in the first pass through rule 704 would not have been triggered but rule 702 would have been triggered and enforced. In a subsequent pass, once rule 702 had been applied, rule 704 would have been triggered and applied, yielding the same end result. In the example shown, other rules not shown in Figures 7A and 7B have been applied to yield a final internal representation 726, for
example, rules to replace the digits "1-7" and "1-3" with the words "seventeen" and "thirteen", respectively.
[0042] Figures 8A and 8B illustrate an example of applying an ordered set of declarative rules to generate an intermediate representation in some embodiments. In this example, referring to Figure 8A a set of declarative rules 800 includes rules of substitution constructed to translate into Spanish information received originally (or transformed in an intermediate operation into) English. The rules shown in Figure 8A may comprise an applicable subset of a broader set of rules, the other members of which are not shown for purposes of simplicity and clarity, and which other rules would not be triggered in the example shown in Figure 8B, for example. As shown in Figure 8B, in this example a series of translations 820 are performed by applying rules 800 in order to an original (or intermediate) representation of the information "the onions" 822. The rules 800 are applied sequentially and in order, for each rule substituting the expression on the left side as shown with the replacement expression on the right side, to yield in the end the translated internal representation 824, i.e., the expression "las cebollas", which is how one communicates the concept of a plurality of onions in Spanish.
[0043] In the example shown in Figures 8A and 8B the internal representation 824 that is shown as being generated include linguistic elements, specifically words, in the target language. In other embodiments, the internal representation may comprise words or other linguistic elements in an original language of the application, for example, or some other language other than the target language. For example, the internal representation
"[_definiteArticle_feminine_plural] [onion_feminine_plural]" may be generated in some embodiments, expressing the information and associated meta-information in English but to be matched in some embodiments to filenames in English of audio files comprising data to render the spoken Spanish words "las" (the feminine plural definite article in Spanish) and "cebollas" (the plural of "onions", which is a feminine noun in Spanish). In some embodiments, use of a common namespace language to express the information to be communicated and associated meta-information, such as communication system rules or meta-information relevant to such rules, for files associated with a plurality of target languages or other communication systems one or more of which may be different from the namespace language, facilitates use of a relative simple and target language/system agnostic
matcher to identify output files that match the internal representation and can be used to render the information in the target communication system and medium.
[0044] Figure 9A illustrates examples of rules of transposition and inheritance in some embodiments. In the example shown, rule 902 provides on the left side as shown that if an adjective immediately preceding a noun that the adjective modifies is encountered, the adjective should be moved to a position immediately following the noun, as is done when translating from English to Spanish for example. Rule 904 provides that if a noun that has gender and grammatical number attributes is followed by an adjective that does not (yet) have such attributes, the adjective inherits the attribute values from the noun that precedes it.
[0045] Figure 9B shows an example that illustrates application of the rules shown in
Figure 9A in an embodiment. A starting representation 920 in English, the words "the red onions" results in the example shown in the representation 922 comprising the Spanish words "las cebollas rojas", in which the feminine plural form of the adjective "red" ("rojas") appears following the noun it modifies ("cebollas" or "onions"). In a system in which the internal representation is in a common language, such as English, but embodies
communication system rules of the target language, even if the target language is not English, the internal representation might look more like [the feminine _plural] [onion feminine _plural] [red_feminine_plural].
[0046] Determining How to Communicate the Information
[0047] In various embodiments, an internal representation of an information to be communicated is received and matched to one or more output data files usable to
communicate the information in a target symbolic communication system (for example, a target spoken language) via a desired medium (e.g., audio output).
[0048] Figure 10 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system via a desired medium. In the example shown, an internal representation that expresses, in a common output file namespace language, information to be communicated in a target language, is received (1002). The internal representation is used to find by filename one or more output files that best match the internal representation (1004). The matched files are rendered to
communicate the information (1006).
[0049] Figure 1 1 is a flow diagram illustrating an embodiment of a process to communicate information in a target symbolic communication system via a desired medium. In some embodiments, the process of Figure 1 1 is used to implement 1004 of Figure 10. In the example shown, a modified "largest match" approach is implemented. Specifically, at each level starting with a top level (i.e., looking for a single file name that matches the entire internal representation), the matcher first looks for a file that is an exact match of the information and meta- information at that level. If no match is found, before descending to the next level of possible match the matcher checks to see if there is a match if one or more elements of meta- information, e.g., one or more meta-information tags, are ignored. For example, files that include complete phrases may not include in their name meta-information such as gender for each or even any words included in the phrase, since such meta- information would not in the case of use of such a file be required to also match correctly corresponding files for definite articles, adjectives, and other modifiers. Referring to Figure 11, the process starts at a top level (1102) and looks for a match at that level (1 104). If a file matching the entire internal representation is found (1 106), that file is used (1108) and the process ends (11 14). If not (1 106), a match is sought at the same level but ignoring for the moment at least certain meta-information, such as grammatical number and/or gender tags (1 110). If a match is found it is used (1108), otherwise the match process descends to a next level down (11 16) and a match (for both information and associated meta-information) is sought at that level (1 114). For example, if the internal representation has three elements and no match for the entire internal representation is found, a file name matching any two adjacent elements is sought. The process of Figure 1 1 continues until files matching all elements comprising the internal representation have been found.
[0050] Figures 12A and 12B illustrate an example of matching an internal representation to one or more output data files in an embodiment. In the example shown, a set of output files 1200 includes audio files 1202, 1204, 1206, 1208, and 1210 as shown. Referring to Figure 12B, the internal representation 1220 is first checked at a top level (entire representation) to seek a match. Since no file named "one_feminine_calorie_to_go" is found, the gender tag "feminine" is ignored temporarily to continue processing at the current level, as shown in modified representation 1222, resulting in a match to file 1202 being found. In this example, the file name is in English but the audio content when rendered is the corresponding spoken phrase in Spanish "una caloria para terminar".
[0051] Figures 12C and 12D illustrate an example of matching an internal representation to one or more output data files in an embodiment. In the example shown, the same output files 1200 as in Figure 12A (shown again in Figure 12C for convenience and clarity) are matched to the internal representation 1240 of Figure 12D. In this example, no file name matches the entire top level representation, either with or without the tag
"feminine" included. At the second level down, in searching for a file name matching three elements of the representation, file 1206 matching the rightmost three elements is found. Finally, at the bottom (one element) level, files 1204 and 1208 matching the first and second elements, respectively, including meta-information, are found, enabling the Spanish phrase "veintiuna calorias para terminar" to be constructed and rendered as audio output. While in the example shown in Figures 12C and 12D separate files match the parts "twenty" and "one (feminine)" to form the contraction "ventiuna", in other embodiments numbers in the range 21-29 might be recorded separately, and separately for the feminine and masculine case of "21" (i.e., "ventiuna" and ventiuno", respectively). In such an embodiment, the internal representation "twenty" adjacent to "one_feminine" would match the file for the contraction "twenty one_feminine", since that would be the largest match, resulting in the translation affording greatest fluency being achieved.
[0052] Figure 13 is a flow diagram illustrating an embodiment of a process to configure a system to communicate information in a target symbolic communication system via a desired medium. In the example shown, output files are received and stored (1302). For example, .aif or other audio files recorded using voice actors to speak words and/or phrases in a target spoken language are received in some embodiments. A list (or other data structure) of file names of the received files is received or generated (1304). A matching logic is configured to use the list of file names to find files that best match a received string or other internal representation of information to be communicated (1306).
[0053] While a number of the examples described above involve communicating information in a target spoken language, techniques described herein may be used to communicate information in other target symbolic communication systems. Such other target symbolic communication systems may include, without limitation, translating from an internal representation comprising a string into a displayed written communication in a target font or language, for example using techniques described herein to select font elements to render ligatures comprising two or more adjacent characters properly using a single vector
graphic or other file; translating from a string embodying note data into pictures of music notes and/or to render as audible music; and selecting based on an internal string
representation tile image files usable to represent two or more different types of terrain, such as to show a land region, a body of water, and a properly rendered coast or other border between them, in one of a plurality of target visual themes or scenarios.
[0054] While a number of the examples described above involve audible
communication, such as spoken language, techniques described herein may be used to communicate information via other media, such as other sensory perceptible output, including without limitation visual display; multi-media displays; haptic technologies, Braille, or other tactile output; or any other sensory perceptible output used to communicate information according to a symbolic communication system.
[0055] Although the foregoing embodiments have been described in some detail for purposes of clarity of understanding, the invention is not limited to the details provided. There are many alternative ways of implementing the invention. The disclosed embodiments are illustrative and not restrictive.
[0056] WHAT IS CLAIMED IS:
Claims
1. A method of providing information, comprising:
receiving information to be communicated as sensory perceptible output; and applying an ordered set of rules to generate a representation that expresses the information in a manner that embodies applicable communication system rules of a target symbolic communication system in which the information is to be communicated.
2. The method of claim 1, wherein the information comprises application information received from an application to be communicated to a user of the application.
3. The method of claim 1, further comprising parsing the information to identify one or more informational elements comprising the information.
4. The method of claim 3, wherein the informational elements comprise one or more of the following: a concept, a number, a unit, and/or one or more words and/or other linguistic units.
5. The method of claim 1, wherein the target symbolic communication system comprises a spoken human language.
6. The method of claim 1, wherein the representation expresses the information in a symbolic communication system other than the target symbolic communication system but deviates from a communication system rule of the symbolic communication system other than the target symbolic communication system to comply instead with a corresponding communication system rule of the target symbolic communication system.
7. The method of claim 6, wherein the corresponding communication system rule of the target symbolic communication system comprises one or more of the following: a syntactic rule; a rule prescribing a word order; a grammar rule; and a rule associated with number or gender.
8. The method of claim 1, wherein the representation expresses the information using a namespace language associated with a set of output files comprising data usable to render a sensory perceptible output.
9. A system, comprising:
an interface configured to receive information to be communicated as sensory perceptible output; and
a processor coupled to the interface and configured to apply an ordered set of rules to generate a representation that expresses the information in a manner that embodies applicable communication system rules of a target symbolic communication system in which the information is to be communicated.
10. The system of claim 9, wherein the information comprises application information received from an application to be communicated to a user of the application.
11. The system of claim 9, wherein the processor is further configured to parse the information to identify one or more informational elements comprising the information.
12. The system of claim 11, wherein the informational elements comprise one or more of the following: a concept, a number, a unit, and/or one or more words and/or other linguistic units.
13. The system of claim 9, wherein the target symbolic communication system comprises a spoken human language.
14. The system of claim 9, wherein the representation expresses the information in a symbolic communication system other than the target symbolic communication system but deviates from a communication system rule of the symbolic communication system other than the target symbolic communication system to comply instead with a corresponding communication system rule of the target symbolic communication system.
15. The system of claim 14, wherein the corresponding communication system rule of the target symbolic communication system comprises one or more of the following: a syntactic rule; a rule prescribing a word order; a grammar rule; and a rule associated with number or gender.
16. The system of claim 9, wherein the representation expresses the information using a namespace language associated with a set of output files comprising data usable to render a sensory perceptible output.
17. A computer program product for providing information, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for: receiving information to be communicated as sensory perceptible output; and applying an ordered set of rules to generate a representation that expresses the information in a manner that embodies applicable communication system rules of a target symbolic communication system in which the information is to be communicated.
18. The computer program product of claim 17, further comprising computer instructions for parsing the information to identify one or more informational elements comprising the information.
19. The computer program product of claim 17, wherein the target symbolic
communication system comprises a spoken human language.
20. The computer program product of claim 17, wherein the representation expresses the information in a symbolic communication system other than the target symbolic
communication system but deviates from a communication system rule of the symbolic communication system other than the target symbolic communication system to comply instead with a corresponding communication system rule of the target symbolic
communication system.
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Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8463053B1 (en) | 2008-08-08 | 2013-06-11 | The Research Foundation Of State University Of New York | Enhanced max margin learning on multimodal data mining in a multimedia database |
US9634855B2 (en) | 2010-05-13 | 2017-04-25 | Alexander Poltorak | Electronic personal interactive device that determines topics of interest using a conversational agent |
DE102011079034A1 (en) | 2011-07-12 | 2013-01-17 | Siemens Aktiengesellschaft | Control of a technical system |
JP6317772B2 (en) | 2013-03-15 | 2018-04-25 | トランスレート アブロード,インコーポレイテッド | System and method for real-time display of foreign language character sets and their translations on resource-constrained mobile devices |
US8965129B2 (en) | 2013-03-15 | 2015-02-24 | Translate Abroad, Inc. | Systems and methods for determining and displaying multi-line foreign language translations in real time on mobile devices |
CN104239343B (en) * | 2013-06-20 | 2018-04-27 | 腾讯科技(深圳)有限公司 | A kind of user inputs the treating method and apparatus of information |
USD749115S1 (en) | 2015-02-20 | 2016-02-09 | Translate Abroad, Inc. | Mobile device with graphical user interface |
US10394958B2 (en) * | 2017-11-09 | 2019-08-27 | Conduent Business Services, Llc | Performing semantic analyses of user-generated text content using a lexicon |
JP2019149124A (en) * | 2018-02-28 | 2019-09-05 | 富士フイルム株式会社 | Conversion device, conversion method, and program |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20030101045A1 (en) * | 2001-11-29 | 2003-05-29 | Peter Moffatt | Method and apparatus for playing recordings of spoken alphanumeric characters |
US20070239429A1 (en) * | 1998-09-25 | 2007-10-11 | Johnson Christopher S | Systems and methods for multiple mode voice and data communications using intelligently bridged TDM and packet buses and methods for implementing language capabilities using the same |
Family Cites Families (573)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3828132A (en) | 1970-10-30 | 1974-08-06 | Bell Telephone Labor Inc | Speech synthesis by concatenation of formant encoded words |
US3704345A (en) | 1971-03-19 | 1972-11-28 | Bell Telephone Labor Inc | Conversion of printed text into synthetic speech |
US3979557A (en) | 1974-07-03 | 1976-09-07 | International Telephone And Telegraph Corporation | Speech processor system for pitch period extraction using prediction filters |
BG24190A1 (en) | 1976-09-08 | 1978-01-10 | Antonov | Method of synthesis of speech and device for effecting same |
JPS597120B2 (en) | 1978-11-24 | 1984-02-16 | 日本電気株式会社 | speech analysis device |
US4310721A (en) | 1980-01-23 | 1982-01-12 | The United States Of America As Represented By The Secretary Of The Army | Half duplex integral vocoder modem system |
US4348553A (en) | 1980-07-02 | 1982-09-07 | International Business Machines Corporation | Parallel pattern verifier with dynamic time warping |
DE3382806T2 (en) | 1982-06-11 | 1996-11-14 | Mitsubishi Electric Corp | Vector quantizer |
US4688195A (en) | 1983-01-28 | 1987-08-18 | Texas Instruments Incorporated | Natural-language interface generating system |
JPS603056A (en) | 1983-06-21 | 1985-01-09 | Toshiba Corp | Information rearranging device |
DE3335358A1 (en) | 1983-09-29 | 1985-04-11 | Siemens AG, 1000 Berlin und 8000 München | METHOD FOR DETERMINING LANGUAGE SPECTRES FOR AUTOMATIC VOICE RECOGNITION AND VOICE ENCODING |
US5164900A (en) | 1983-11-14 | 1992-11-17 | Colman Bernath | Method and device for phonetically encoding Chinese textual data for data processing entry |
US4726065A (en) | 1984-01-26 | 1988-02-16 | Horst Froessl | Image manipulation by speech signals |
US4955047A (en) | 1984-03-26 | 1990-09-04 | Dytel Corporation | Automated attendant with direct inward system access |
US4811243A (en) | 1984-04-06 | 1989-03-07 | Racine Marsh V | Computer aided coordinate digitizing system |
US4692941A (en) | 1984-04-10 | 1987-09-08 | First Byte | Real-time text-to-speech conversion system |
US4783807A (en) | 1984-08-27 | 1988-11-08 | John Marley | System and method for sound recognition with feature selection synchronized to voice pitch |
US4718094A (en) | 1984-11-19 | 1988-01-05 | International Business Machines Corp. | Speech recognition system |
US5165007A (en) | 1985-02-01 | 1992-11-17 | International Business Machines Corporation | Feneme-based Markov models for words |
US4944013A (en) | 1985-04-03 | 1990-07-24 | British Telecommunications Public Limited Company | Multi-pulse speech coder |
US4819271A (en) | 1985-05-29 | 1989-04-04 | International Business Machines Corporation | Constructing Markov model word baseforms from multiple utterances by concatenating model sequences for word segments |
US4833712A (en) | 1985-05-29 | 1989-05-23 | International Business Machines Corporation | Automatic generation of simple Markov model stunted baseforms for words in a vocabulary |
EP0218859A3 (en) | 1985-10-11 | 1989-09-06 | International Business Machines Corporation | Signal processor communication interface |
US4776016A (en) | 1985-11-21 | 1988-10-04 | Position Orientation Systems, Inc. | Voice control system |
JPH0833744B2 (en) | 1986-01-09 | 1996-03-29 | 株式会社東芝 | Speech synthesizer |
US4724542A (en) | 1986-01-22 | 1988-02-09 | International Business Machines Corporation | Automatic reference adaptation during dynamic signature verification |
US5759101A (en) | 1986-03-10 | 1998-06-02 | Response Reward Systems L.C. | Central and remote evaluation of responses of participatory broadcast audience with automatic crediting and couponing |
US5057915A (en) | 1986-03-10 | 1991-10-15 | Kohorn H Von | System and method for attracting shoppers to sales outlets |
US5032989A (en) | 1986-03-19 | 1991-07-16 | Realpro, Ltd. | Real estate search and location system and method |
DE3779351D1 (en) | 1986-03-28 | 1992-07-02 | American Telephone And Telegraph Co., New York, N.Y., Us | |
US4903305A (en) | 1986-05-12 | 1990-02-20 | Dragon Systems, Inc. | Method for representing word models for use in speech recognition |
EP0262938B1 (en) | 1986-10-03 | 1993-12-15 | BRITISH TELECOMMUNICATIONS public limited company | Language translation system |
US4878230A (en) | 1986-10-16 | 1989-10-31 | Mitsubishi Denki Kabushiki Kaisha | Amplitude-adaptive vector quantization system |
US4829576A (en) | 1986-10-21 | 1989-05-09 | Dragon Systems, Inc. | Voice recognition system |
US4852168A (en) | 1986-11-18 | 1989-07-25 | Sprague Richard P | Compression of stored waveforms for artificial speech |
US4727354A (en) | 1987-01-07 | 1988-02-23 | Unisys Corporation | System for selecting best fit vector code in vector quantization encoding |
US4827520A (en) | 1987-01-16 | 1989-05-02 | Prince Corporation | Voice actuated control system for use in a vehicle |
US4965763A (en) | 1987-03-03 | 1990-10-23 | International Business Machines Corporation | Computer method for automatic extraction of commonly specified information from business correspondence |
US5644727A (en) | 1987-04-15 | 1997-07-01 | Proprietary Financial Products, Inc. | System for the operation and management of one or more financial accounts through the use of a digital communication and computation system for exchange, investment and borrowing |
EP0293259A3 (en) | 1987-05-29 | 1990-03-07 | Kabushiki Kaisha Toshiba | Voice recognition system used in telephone apparatus |
DE3723078A1 (en) | 1987-07-11 | 1989-01-19 | Philips Patentverwaltung | METHOD FOR DETECTING CONTINUOUSLY SPOKEN WORDS |
CA1288516C (en) | 1987-07-31 | 1991-09-03 | Leendert M. Bijnagte | Apparatus and method for communicating textual and image information between a host computer and a remote display terminal |
US4974191A (en) | 1987-07-31 | 1990-11-27 | Syntellect Software Inc. | Adaptive natural language computer interface system |
US5022081A (en) | 1987-10-01 | 1991-06-04 | Sharp Kabushiki Kaisha | Information recognition system |
US4852173A (en) | 1987-10-29 | 1989-07-25 | International Business Machines Corporation | Design and construction of a binary-tree system for language modelling |
US5072452A (en) | 1987-10-30 | 1991-12-10 | International Business Machines Corporation | Automatic determination of labels and Markov word models in a speech recognition system |
DE3876379T2 (en) | 1987-10-30 | 1993-06-09 | Ibm | AUTOMATIC DETERMINATION OF LABELS AND MARKOV WORD MODELS IN A VOICE RECOGNITION SYSTEM. |
US4914586A (en) | 1987-11-06 | 1990-04-03 | Xerox Corporation | Garbage collector for hypermedia systems |
US4992972A (en) | 1987-11-18 | 1991-02-12 | International Business Machines Corporation | Flexible context searchable on-line information system with help files and modules for on-line computer system documentation |
US5220657A (en) | 1987-12-02 | 1993-06-15 | Xerox Corporation | Updating local copy of shared data in a collaborative system |
US4984177A (en) | 1988-02-05 | 1991-01-08 | Advanced Products And Technologies, Inc. | Voice language translator |
CA1333420C (en) | 1988-02-29 | 1994-12-06 | Tokumichi Murakami | Vector quantizer |
US4914590A (en) | 1988-05-18 | 1990-04-03 | Emhart Industries, Inc. | Natural language understanding system |
FR2636163B1 (en) | 1988-09-02 | 1991-07-05 | Hamon Christian | METHOD AND DEVICE FOR SYNTHESIZING SPEECH BY ADDING-COVERING WAVEFORMS |
US4839853A (en) | 1988-09-15 | 1989-06-13 | Bell Communications Research, Inc. | Computer information retrieval using latent semantic structure |
JPH0293597A (en) | 1988-09-30 | 1990-04-04 | Nippon I B M Kk | Speech recognition device |
US4905163A (en) | 1988-10-03 | 1990-02-27 | Minnesota Mining & Manufacturing Company | Intelligent optical navigator dynamic information presentation and navigation system |
US5282265A (en) | 1988-10-04 | 1994-01-25 | Canon Kabushiki Kaisha | Knowledge information processing system |
DE3837590A1 (en) | 1988-11-05 | 1990-05-10 | Ant Nachrichtentech | PROCESS FOR REDUCING THE DATA RATE OF DIGITAL IMAGE DATA |
ATE102731T1 (en) | 1988-11-23 | 1994-03-15 | Digital Equipment Corp | NAME PRONUNCIATION BY A SYNTHETIC. |
US5027406A (en) | 1988-12-06 | 1991-06-25 | Dragon Systems, Inc. | Method for interactive speech recognition and training |
US5127055A (en) | 1988-12-30 | 1992-06-30 | Kurzweil Applied Intelligence, Inc. | Speech recognition apparatus & method having dynamic reference pattern adaptation |
US5293448A (en) | 1989-10-02 | 1994-03-08 | Nippon Telegraph And Telephone Corporation | Speech analysis-synthesis method and apparatus therefor |
US5047614A (en) | 1989-01-23 | 1991-09-10 | Bianco James S | Method and apparatus for computer-aided shopping |
SE466029B (en) | 1989-03-06 | 1991-12-02 | Ibm Svenska Ab | DEVICE AND PROCEDURE FOR ANALYSIS OF NATURAL LANGUAGES IN A COMPUTER-BASED INFORMATION PROCESSING SYSTEM |
JPH0782544B2 (en) | 1989-03-24 | 1995-09-06 | インターナショナル・ビジネス・マシーンズ・コーポレーション | DP matching method and apparatus using multi-template |
US4977598A (en) | 1989-04-13 | 1990-12-11 | Texas Instruments Incorporated | Efficient pruning algorithm for hidden markov model speech recognition |
US5197005A (en) | 1989-05-01 | 1993-03-23 | Intelligent Business Systems | Database retrieval system having a natural language interface |
US5010574A (en) | 1989-06-13 | 1991-04-23 | At&T Bell Laboratories | Vector quantizer search arrangement |
JP2940005B2 (en) | 1989-07-20 | 1999-08-25 | 日本電気株式会社 | Audio coding device |
US5091945A (en) | 1989-09-28 | 1992-02-25 | At&T Bell Laboratories | Source dependent channel coding with error protection |
CA2027705C (en) | 1989-10-17 | 1994-02-15 | Masami Akamine | Speech coding system utilizing a recursive computation technique for improvement in processing speed |
US5020112A (en) | 1989-10-31 | 1991-05-28 | At&T Bell Laboratories | Image recognition method using two-dimensional stochastic grammars |
US5220639A (en) | 1989-12-01 | 1993-06-15 | National Science Council | Mandarin speech input method for Chinese computers and a mandarin speech recognition machine |
US5021971A (en) | 1989-12-07 | 1991-06-04 | Unisys Corporation | Reflective binary encoder for vector quantization |
US5179652A (en) | 1989-12-13 | 1993-01-12 | Anthony I. Rozmanith | Method and apparatus for storing, transmitting and retrieving graphical and tabular data |
CH681573A5 (en) | 1990-02-13 | 1993-04-15 | Astral | Automatic teller arrangement involving bank computers - is operated by user data card carrying personal data, account information and transaction records |
US5208862A (en) | 1990-02-22 | 1993-05-04 | Nec Corporation | Speech coder |
US5301109A (en) | 1990-06-11 | 1994-04-05 | Bell Communications Research, Inc. | Computerized cross-language document retrieval using latent semantic indexing |
JP3266246B2 (en) | 1990-06-15 | 2002-03-18 | インターナシヨナル・ビジネス・マシーンズ・コーポレーシヨン | Natural language analysis apparatus and method, and knowledge base construction method for natural language analysis |
US5202952A (en) | 1990-06-22 | 1993-04-13 | Dragon Systems, Inc. | Large-vocabulary continuous speech prefiltering and processing system |
GB9017600D0 (en) | 1990-08-10 | 1990-09-26 | British Aerospace | An assembly and method for binary tree-searched vector quanisation data compression processing |
US5404295A (en) | 1990-08-16 | 1995-04-04 | Katz; Boris | Method and apparatus for utilizing annotations to facilitate computer retrieval of database material |
US5309359A (en) | 1990-08-16 | 1994-05-03 | Boris Katz | Method and apparatus for generating and utlizing annotations to facilitate computer text retrieval |
US5297170A (en) | 1990-08-21 | 1994-03-22 | Codex Corporation | Lattice and trellis-coded quantization |
US5400434A (en) | 1990-09-04 | 1995-03-21 | Matsushita Electric Industrial Co., Ltd. | Voice source for synthetic speech system |
US5216747A (en) | 1990-09-20 | 1993-06-01 | Digital Voice Systems, Inc. | Voiced/unvoiced estimation of an acoustic signal |
US5128672A (en) | 1990-10-30 | 1992-07-07 | Apple Computer, Inc. | Dynamic predictive keyboard |
US5325298A (en) | 1990-11-07 | 1994-06-28 | Hnc, Inc. | Methods for generating or revising context vectors for a plurality of word stems |
US5317507A (en) | 1990-11-07 | 1994-05-31 | Gallant Stephen I | Method for document retrieval and for word sense disambiguation using neural networks |
US5247579A (en) | 1990-12-05 | 1993-09-21 | Digital Voice Systems, Inc. | Methods for speech transmission |
US5345536A (en) | 1990-12-21 | 1994-09-06 | Matsushita Electric Industrial Co., Ltd. | Method of speech recognition |
US5127053A (en) | 1990-12-24 | 1992-06-30 | General Electric Company | Low-complexity method for improving the performance of autocorrelation-based pitch detectors |
US5133011A (en) | 1990-12-26 | 1992-07-21 | International Business Machines Corporation | Method and apparatus for linear vocal control of cursor position |
US5268990A (en) | 1991-01-31 | 1993-12-07 | Sri International | Method for recognizing speech using linguistically-motivated hidden Markov models |
GB9105367D0 (en) | 1991-03-13 | 1991-04-24 | Univ Strathclyde | Computerised information-retrieval database systems |
US5303406A (en) | 1991-04-29 | 1994-04-12 | Motorola, Inc. | Noise squelch circuit with adaptive noise shaping |
US5475587A (en) | 1991-06-28 | 1995-12-12 | Digital Equipment Corporation | Method and apparatus for efficient morphological text analysis using a high-level language for compact specification of inflectional paradigms |
US5293452A (en) | 1991-07-01 | 1994-03-08 | Texas Instruments Incorporated | Voice log-in using spoken name input |
US5687077A (en) | 1991-07-31 | 1997-11-11 | Universal Dynamics Limited | Method and apparatus for adaptive control |
US5199077A (en) | 1991-09-19 | 1993-03-30 | Xerox Corporation | Wordspotting for voice editing and indexing |
JP2662120B2 (en) | 1991-10-01 | 1997-10-08 | インターナショナル・ビジネス・マシーンズ・コーポレイション | Speech recognition device and processing unit for speech recognition |
US5222146A (en) | 1991-10-23 | 1993-06-22 | International Business Machines Corporation | Speech recognition apparatus having a speech coder outputting acoustic prototype ranks |
KR940002854B1 (en) | 1991-11-06 | 1994-04-04 | 한국전기통신공사 | Sound synthesizing system |
US5386494A (en) | 1991-12-06 | 1995-01-31 | Apple Computer, Inc. | Method and apparatus for controlling a speech recognition function using a cursor control device |
US5903454A (en) | 1991-12-23 | 1999-05-11 | Hoffberg; Linda Irene | Human-factored interface corporating adaptive pattern recognition based controller apparatus |
US6081750A (en) | 1991-12-23 | 2000-06-27 | Hoffberg; Steven Mark | Ergonomic man-machine interface incorporating adaptive pattern recognition based control system |
US5502790A (en) | 1991-12-24 | 1996-03-26 | Oki Electric Industry Co., Ltd. | Speech recognition method and system using triphones, diphones, and phonemes |
US5349645A (en) | 1991-12-31 | 1994-09-20 | Matsushita Electric Industrial Co., Ltd. | Word hypothesizer for continuous speech decoding using stressed-vowel centered bidirectional tree searches |
US5267345A (en) | 1992-02-10 | 1993-11-30 | International Business Machines Corporation | Speech recognition apparatus which predicts word classes from context and words from word classes |
ES2128390T3 (en) | 1992-03-02 | 1999-05-16 | At & T Corp | TRAINING METHOD AND DEVICE FOR VOICE RECOGNITION. |
US6055514A (en) | 1992-03-20 | 2000-04-25 | Wren; Stephen Corey | System for marketing foods and services utilizing computerized centraland remote facilities |
US5317647A (en) | 1992-04-07 | 1994-05-31 | Apple Computer, Inc. | Constrained attribute grammars for syntactic pattern recognition |
US5412804A (en) | 1992-04-30 | 1995-05-02 | Oracle Corporation | Extending the semantics of the outer join operator for un-nesting queries to a data base |
US5293584A (en) | 1992-05-21 | 1994-03-08 | International Business Machines Corporation | Speech recognition system for natural language translation |
US5434777A (en) | 1992-05-27 | 1995-07-18 | Apple Computer, Inc. | Method and apparatus for processing natural language |
US5390281A (en) | 1992-05-27 | 1995-02-14 | Apple Computer, Inc. | Method and apparatus for deducing user intent and providing computer implemented services |
US5734789A (en) | 1992-06-01 | 1998-03-31 | Hughes Electronics | Voiced, unvoiced or noise modes in a CELP vocoder |
US5333275A (en) | 1992-06-23 | 1994-07-26 | Wheatley Barbara J | System and method for time aligning speech |
US5325297A (en) | 1992-06-25 | 1994-06-28 | System Of Multiple-Colored Images For Internationally Listed Estates, Inc. | Computer implemented method and system for storing and retrieving textual data and compressed image data |
US5999908A (en) | 1992-08-06 | 1999-12-07 | Abelow; Daniel H. | Customer-based product design module |
US5412806A (en) | 1992-08-20 | 1995-05-02 | Hewlett-Packard Company | Calibration of logical cost formulae for queries in a heterogeneous DBMS using synthetic database |
GB9220404D0 (en) | 1992-08-20 | 1992-11-11 | Nat Security Agency | Method of identifying,retrieving and sorting documents |
US5333236A (en) | 1992-09-10 | 1994-07-26 | International Business Machines Corporation | Speech recognizer having a speech coder for an acoustic match based on context-dependent speech-transition acoustic models |
US5384893A (en) | 1992-09-23 | 1995-01-24 | Emerson & Stern Associates, Inc. | Method and apparatus for speech synthesis based on prosodic analysis |
FR2696036B1 (en) | 1992-09-24 | 1994-10-14 | France Telecom | Method of measuring resemblance between sound samples and device for implementing this method. |
JPH0772840B2 (en) | 1992-09-29 | 1995-08-02 | 日本アイ・ビー・エム株式会社 | Speech model configuration method, speech recognition method, speech recognition device, and speech model training method |
US5758313A (en) | 1992-10-16 | 1998-05-26 | Mobile Information Systems, Inc. | Method and apparatus for tracking vehicle location |
US5455888A (en) | 1992-12-04 | 1995-10-03 | Northern Telecom Limited | Speech bandwidth extension method and apparatus |
US5412756A (en) | 1992-12-22 | 1995-05-02 | Mitsubishi Denki Kabushiki Kaisha | Artificial intelligence software shell for plant operation simulation |
US5613036A (en) | 1992-12-31 | 1997-03-18 | Apple Computer, Inc. | Dynamic categories for a speech recognition system |
US5384892A (en) | 1992-12-31 | 1995-01-24 | Apple Computer, Inc. | Dynamic language model for speech recognition |
US5734791A (en) | 1992-12-31 | 1998-03-31 | Apple Computer, Inc. | Rapid tree-based method for vector quantization |
US5390279A (en) | 1992-12-31 | 1995-02-14 | Apple Computer, Inc. | Partitioning speech rules by context for speech recognition |
US6122616A (en) | 1993-01-21 | 2000-09-19 | Apple Computer, Inc. | Method and apparatus for diphone aliasing |
US5864844A (en) | 1993-02-18 | 1999-01-26 | Apple Computer, Inc. | System and method for enhancing a user interface with a computer based training tool |
CA2091658A1 (en) | 1993-03-15 | 1994-09-16 | Matthew Lennig | Method and apparatus for automation of directory assistance using speech recognition |
US6055531A (en) | 1993-03-24 | 2000-04-25 | Engate Incorporated | Down-line transcription system having context sensitive searching capability |
US5536902A (en) | 1993-04-14 | 1996-07-16 | Yamaha Corporation | Method of and apparatus for analyzing and synthesizing a sound by extracting and controlling a sound parameter |
US5444823A (en) | 1993-04-16 | 1995-08-22 | Compaq Computer Corporation | Intelligent search engine for associated on-line documentation having questionless case-based knowledge base |
US5574823A (en) | 1993-06-23 | 1996-11-12 | Her Majesty The Queen In Right Of Canada As Represented By The Minister Of Communications | Frequency selective harmonic coding |
US5515475A (en) | 1993-06-24 | 1996-05-07 | Northern Telecom Limited | Speech recognition method using a two-pass search |
JPH0756933A (en) | 1993-06-24 | 1995-03-03 | Xerox Corp | Method for retrieval of document |
JP3685812B2 (en) | 1993-06-29 | 2005-08-24 | ソニー株式会社 | Audio signal transmitter / receiver |
US5794207A (en) | 1996-09-04 | 1998-08-11 | Walker Asset Management Limited Partnership | Method and apparatus for a cryptographically assisted commercial network system designed to facilitate buyer-driven conditional purchase offers |
US5495604A (en) | 1993-08-25 | 1996-02-27 | Asymetrix Corporation | Method and apparatus for the modeling and query of database structures using natural language-like constructs |
US5619694A (en) | 1993-08-26 | 1997-04-08 | Nec Corporation | Case database storage/retrieval system |
US5940811A (en) | 1993-08-27 | 1999-08-17 | Affinity Technology Group, Inc. | Closed loop financial transaction method and apparatus |
US5377258A (en) | 1993-08-30 | 1994-12-27 | National Medical Research Council | Method and apparatus for an automated and interactive behavioral guidance system |
US5873056A (en) | 1993-10-12 | 1999-02-16 | The Syracuse University | Natural language processing system for semantic vector representation which accounts for lexical ambiguity |
US5578808A (en) | 1993-12-22 | 1996-11-26 | Datamark Services, Inc. | Data card that can be used for transactions involving separate card issuers |
CA2179523A1 (en) | 1993-12-23 | 1995-06-29 | David A. Boulton | Method and apparatus for implementing user feedback |
US5621859A (en) | 1994-01-19 | 1997-04-15 | Bbn Corporation | Single tree method for grammar directed, very large vocabulary speech recognizer |
US5584024A (en) | 1994-03-24 | 1996-12-10 | Software Ag | Interactive database query system and method for prohibiting the selection of semantically incorrect query parameters |
US5642519A (en) | 1994-04-29 | 1997-06-24 | Sun Microsystems, Inc. | Speech interpreter with a unified grammer compiler |
DE69520302T2 (en) | 1994-05-25 | 2001-08-09 | Victor Company Of Japan | Data transfer device with variable transmission rate |
US5493677A (en) | 1994-06-08 | 1996-02-20 | Systems Research & Applications Corporation | Generation, archiving, and retrieval of digital images with evoked suggestion-set captions and natural language interface |
US5675819A (en) | 1994-06-16 | 1997-10-07 | Xerox Corporation | Document information retrieval using global word co-occurrence patterns |
JPH0869470A (en) | 1994-06-21 | 1996-03-12 | Canon Inc | Natural language processing device and method |
US5948040A (en) | 1994-06-24 | 1999-09-07 | Delorme Publishing Co. | Travel reservation information and planning system |
US5682539A (en) | 1994-09-29 | 1997-10-28 | Conrad; Donovan | Anticipated meaning natural language interface |
US5715468A (en) | 1994-09-30 | 1998-02-03 | Budzinski; Robert Lucius | Memory system for storing and retrieving experience and knowledge with natural language |
GB2293667B (en) | 1994-09-30 | 1998-05-27 | Intermation Limited | Database management system |
US5845255A (en) | 1994-10-28 | 1998-12-01 | Advanced Health Med-E-Systems Corporation | Prescription management system |
US5577241A (en) | 1994-12-07 | 1996-11-19 | Excite, Inc. | Information retrieval system and method with implementation extensible query architecture |
US5748974A (en) | 1994-12-13 | 1998-05-05 | International Business Machines Corporation | Multimodal natural language interface for cross-application tasks |
US5794050A (en) | 1995-01-04 | 1998-08-11 | Intelligent Text Processing, Inc. | Natural language understanding system |
EP1431864B2 (en) | 1995-02-13 | 2012-08-22 | Intertrust Technologies Corporation | Systems and methods for secure transaction management and electronic rights protection |
US5701400A (en) | 1995-03-08 | 1997-12-23 | Amado; Carlos Armando | Method and apparatus for applying if-then-else rules to data sets in a relational data base and generating from the results of application of said rules a database of diagnostics linked to said data sets to aid executive analysis of financial data |
US5749081A (en) | 1995-04-06 | 1998-05-05 | Firefly Network, Inc. | System and method for recommending items to a user |
US5642464A (en) | 1995-05-03 | 1997-06-24 | Northern Telecom Limited | Methods and apparatus for noise conditioning in digital speech compression systems using linear predictive coding |
US5664055A (en) | 1995-06-07 | 1997-09-02 | Lucent Technologies Inc. | CS-ACELP speech compression system with adaptive pitch prediction filter gain based on a measure of periodicity |
US5710886A (en) | 1995-06-16 | 1998-01-20 | Sellectsoft, L.C. | Electric couponing method and apparatus |
JP3284832B2 (en) | 1995-06-22 | 2002-05-20 | セイコーエプソン株式会社 | Speech recognition dialogue processing method and speech recognition dialogue device |
US6038533A (en) | 1995-07-07 | 2000-03-14 | Lucent Technologies Inc. | System and method for selecting training text |
US6026388A (en) | 1995-08-16 | 2000-02-15 | Textwise, Llc | User interface and other enhancements for natural language information retrieval system and method |
JP3697748B2 (en) | 1995-08-21 | 2005-09-21 | セイコーエプソン株式会社 | Terminal, voice recognition device |
US5712957A (en) | 1995-09-08 | 1998-01-27 | Carnegie Mellon University | Locating and correcting erroneously recognized portions of utterances by rescoring based on two n-best lists |
US5790978A (en) | 1995-09-15 | 1998-08-04 | Lucent Technologies, Inc. | System and method for determining pitch contours |
US6173261B1 (en) | 1998-09-30 | 2001-01-09 | At&T Corp | Grammar fragment acquisition using syntactic and semantic clustering |
US5737734A (en) | 1995-09-15 | 1998-04-07 | Infonautics Corporation | Query word relevance adjustment in a search of an information retrieval system |
US5884323A (en) | 1995-10-13 | 1999-03-16 | 3Com Corporation | Extendible method and apparatus for synchronizing files on two different computer systems |
US5799276A (en) | 1995-11-07 | 1998-08-25 | Accent Incorporated | Knowledge-based speech recognition system and methods having frame length computed based upon estimated pitch period of vocalic intervals |
US5794237A (en) | 1995-11-13 | 1998-08-11 | International Business Machines Corporation | System and method for improving problem source identification in computer systems employing relevance feedback and statistical source ranking |
US5706442A (en) | 1995-12-20 | 1998-01-06 | Block Financial Corporation | System for on-line financial services using distributed objects |
US6119101A (en) | 1996-01-17 | 2000-09-12 | Personal Agents, Inc. | Intelligent agents for electronic commerce |
US6125356A (en) | 1996-01-18 | 2000-09-26 | Rosefaire Development, Ltd. | Portable sales presentation system with selective scripted seller prompts |
US5987404A (en) | 1996-01-29 | 1999-11-16 | International Business Machines Corporation | Statistical natural language understanding using hidden clumpings |
US5729694A (en) | 1996-02-06 | 1998-03-17 | The Regents Of The University Of California | Speech coding, reconstruction and recognition using acoustics and electromagnetic waves |
US6076088A (en) | 1996-02-09 | 2000-06-13 | Paik; Woojin | Information extraction system and method using concept relation concept (CRC) triples |
US5835893A (en) | 1996-02-15 | 1998-11-10 | Atr Interpreting Telecommunications Research Labs | Class-based word clustering for speech recognition using a three-level balanced hierarchical similarity |
US5901287A (en) | 1996-04-01 | 1999-05-04 | The Sabre Group Inc. | Information aggregation and synthesization system |
US5867799A (en) | 1996-04-04 | 1999-02-02 | Lang; Andrew K. | Information system and method for filtering a massive flow of information entities to meet user information classification needs |
US5987140A (en) | 1996-04-26 | 1999-11-16 | Verifone, Inc. | System, method and article of manufacture for secure network electronic payment and credit collection |
US5963924A (en) | 1996-04-26 | 1999-10-05 | Verifone, Inc. | System, method and article of manufacture for the use of payment instrument holders and payment instruments in network electronic commerce |
US5913193A (en) | 1996-04-30 | 1999-06-15 | Microsoft Corporation | Method and system of runtime acoustic unit selection for speech synthesis |
US5857184A (en) | 1996-05-03 | 1999-01-05 | Walden Media, Inc. | Language and method for creating, organizing, and retrieving data from a database |
US5828999A (en) | 1996-05-06 | 1998-10-27 | Apple Computer, Inc. | Method and system for deriving a large-span semantic language model for large-vocabulary recognition systems |
FR2748342B1 (en) | 1996-05-06 | 1998-07-17 | France Telecom | METHOD AND DEVICE FOR FILTERING A SPEECH SIGNAL BY EQUALIZATION, USING A STATISTICAL MODEL OF THIS SIGNAL |
US5826261A (en) | 1996-05-10 | 1998-10-20 | Spencer; Graham | System and method for querying multiple, distributed databases by selective sharing of local relative significance information for terms related to the query |
US6366883B1 (en) | 1996-05-15 | 2002-04-02 | Atr Interpreting Telecommunications | Concatenation of speech segments by use of a speech synthesizer |
US5727950A (en) | 1996-05-22 | 1998-03-17 | Netsage Corporation | Agent based instruction system and method |
US5966533A (en) | 1996-06-11 | 1999-10-12 | Excite, Inc. | Method and system for dynamically synthesizing a computer program by differentially resolving atoms based on user context data |
US5915249A (en) | 1996-06-14 | 1999-06-22 | Excite, Inc. | System and method for accelerated query evaluation of very large full-text databases |
US5987132A (en) | 1996-06-17 | 1999-11-16 | Verifone, Inc. | System, method and article of manufacture for conditionally accepting a payment method utilizing an extensible, flexible architecture |
US5825881A (en) | 1996-06-28 | 1998-10-20 | Allsoft Distributing Inc. | Public network merchandising system |
US6070147A (en) | 1996-07-02 | 2000-05-30 | Tecmark Services, Inc. | Customer identification and marketing analysis systems |
EP0912954B8 (en) | 1996-07-22 | 2006-06-14 | Cyva Research Corporation | Personal information security and exchange tool |
US5862223A (en) | 1996-07-24 | 1999-01-19 | Walker Asset Management Limited Partnership | Method and apparatus for a cryptographically-assisted commercial network system designed to facilitate and support expert-based commerce |
EP0829811A1 (en) | 1996-09-11 | 1998-03-18 | Nippon Telegraph And Telephone Corporation | Method and system for information retrieval |
US6181935B1 (en) | 1996-09-27 | 2001-01-30 | Software.Com, Inc. | Mobility extended telephone application programming interface and method of use |
US5794182A (en) | 1996-09-30 | 1998-08-11 | Apple Computer, Inc. | Linear predictive speech encoding systems with efficient combination pitch coefficients computation |
US5721827A (en) | 1996-10-02 | 1998-02-24 | James Logan | System for electrically distributing personalized information |
US5913203A (en) | 1996-10-03 | 1999-06-15 | Jaesent Inc. | System and method for pseudo cash transactions |
US5930769A (en) | 1996-10-07 | 1999-07-27 | Rose; Andrea | System and method for fashion shopping |
US5836771A (en) | 1996-12-02 | 1998-11-17 | Ho; Chi Fai | Learning method and system based on questioning |
US6665639B2 (en) | 1996-12-06 | 2003-12-16 | Sensory, Inc. | Speech recognition in consumer electronic products |
US6078914A (en) | 1996-12-09 | 2000-06-20 | Open Text Corporation | Natural language meta-search system and method |
US5839106A (en) | 1996-12-17 | 1998-11-17 | Apple Computer, Inc. | Large-vocabulary speech recognition using an integrated syntactic and semantic statistical language model |
US5966126A (en) | 1996-12-23 | 1999-10-12 | Szabo; Andrew J. | Graphic user interface for database system |
US5932869A (en) | 1996-12-27 | 1999-08-03 | Graphic Technology, Inc. | Promotional system with magnetic stripe and visual thermo-reversible print surfaced medium |
JP3579204B2 (en) | 1997-01-17 | 2004-10-20 | 富士通株式会社 | Document summarizing apparatus and method |
US5941944A (en) | 1997-03-03 | 1999-08-24 | Microsoft Corporation | Method for providing a substitute for a requested inaccessible object by identifying substantially similar objects using weights corresponding to object features |
US6076051A (en) | 1997-03-07 | 2000-06-13 | Microsoft Corporation | Information retrieval utilizing semantic representation of text |
US5930801A (en) | 1997-03-07 | 1999-07-27 | Xerox Corporation | Shared-data environment in which each file has independent security properties |
US5822743A (en) | 1997-04-08 | 1998-10-13 | 1215627 Ontario Inc. | Knowledge-based information retrieval system |
US5970474A (en) | 1997-04-24 | 1999-10-19 | Sears, Roebuck And Co. | Registry information system for shoppers |
US5895464A (en) | 1997-04-30 | 1999-04-20 | Eastman Kodak Company | Computer program product and a method for using natural language for the description, search and retrieval of multi-media objects |
US5860063A (en) | 1997-07-11 | 1999-01-12 | At&T Corp | Automated meaningful phrase clustering |
US5933822A (en) | 1997-07-22 | 1999-08-03 | Microsoft Corporation | Apparatus and methods for an information retrieval system that employs natural language processing of search results to improve overall precision |
US5974146A (en) | 1997-07-30 | 1999-10-26 | Huntington Bancshares Incorporated | Real time bank-centric universal payment system |
US5895466A (en) | 1997-08-19 | 1999-04-20 | At&T Corp | Automated natural language understanding customer service system |
US6081774A (en) | 1997-08-22 | 2000-06-27 | Novell, Inc. | Natural language information retrieval system and method |
US6404876B1 (en) | 1997-09-25 | 2002-06-11 | Gte Intelligent Network Services Incorporated | System and method for voice activated dialing and routing under open access network control |
US6023684A (en) | 1997-10-01 | 2000-02-08 | Security First Technologies, Inc. | Three tier financial transaction system with cache memory |
EP0911808B1 (en) | 1997-10-23 | 2002-05-08 | Sony International (Europe) GmbH | Speech interface in a home network environment |
US6108627A (en) | 1997-10-31 | 2000-08-22 | Nortel Networks Corporation | Automatic transcription tool |
US5943670A (en) | 1997-11-21 | 1999-08-24 | International Business Machines Corporation | System and method for categorizing objects in combined categories |
US5960422A (en) | 1997-11-26 | 1999-09-28 | International Business Machines Corporation | System and method for optimized source selection in an information retrieval system |
US6026375A (en) | 1997-12-05 | 2000-02-15 | Nortel Networks Corporation | Method and apparatus for processing orders from customers in a mobile environment |
US6064960A (en) | 1997-12-18 | 2000-05-16 | Apple Computer, Inc. | Method and apparatus for improved duration modeling of phonemes |
US6094649A (en) | 1997-12-22 | 2000-07-25 | Partnet, Inc. | Keyword searches of structured databases |
US6173287B1 (en) | 1998-03-11 | 2001-01-09 | Digital Equipment Corporation | Technique for ranking multimedia annotations of interest |
US6195641B1 (en) | 1998-03-27 | 2001-02-27 | International Business Machines Corp. | Network universal spoken language vocabulary |
US6026393A (en) | 1998-03-31 | 2000-02-15 | Casebank Technologies Inc. | Configuration knowledge as an aid to case retrieval |
US6233559B1 (en) | 1998-04-01 | 2001-05-15 | Motorola, Inc. | Speech control of multiple applications using applets |
US6173279B1 (en) | 1998-04-09 | 2001-01-09 | At&T Corp. | Method of using a natural language interface to retrieve information from one or more data resources |
US6088731A (en) | 1998-04-24 | 2000-07-11 | Associative Computing, Inc. | Intelligent assistant for use with a local computer and with the internet |
US6016471A (en) | 1998-04-29 | 2000-01-18 | Matsushita Electric Industrial Co., Ltd. | Method and apparatus using decision trees to generate and score multiple pronunciations for a spelled word |
US6029132A (en) | 1998-04-30 | 2000-02-22 | Matsushita Electric Industrial Co. | Method for letter-to-sound in text-to-speech synthesis |
US6285786B1 (en) | 1998-04-30 | 2001-09-04 | Motorola, Inc. | Text recognizer and method using non-cumulative character scoring in a forward search |
US6144938A (en) | 1998-05-01 | 2000-11-07 | Sun Microsystems, Inc. | Voice user interface with personality |
US7526466B2 (en) | 1998-05-28 | 2009-04-28 | Qps Tech Limited Liability Company | Method and system for analysis of intended meaning of natural language |
US7711672B2 (en) | 1998-05-28 | 2010-05-04 | Lawrence Au | Semantic network methods to disambiguate natural language meaning |
US6778970B2 (en) | 1998-05-28 | 2004-08-17 | Lawrence Au | Topological methods to organize semantic network data flows for conversational applications |
US6144958A (en) | 1998-07-15 | 2000-11-07 | Amazon.Com, Inc. | System and method for correcting spelling errors in search queries |
US6105865A (en) | 1998-07-17 | 2000-08-22 | Hardesty; Laurence Daniel | Financial transaction system with retirement saving benefit |
US6499013B1 (en) | 1998-09-09 | 2002-12-24 | One Voice Technologies, Inc. | Interactive user interface using speech recognition and natural language processing |
US6434524B1 (en) | 1998-09-09 | 2002-08-13 | One Voice Technologies, Inc. | Object interactive user interface using speech recognition and natural language processing |
US6792082B1 (en) | 1998-09-11 | 2004-09-14 | Comverse Ltd. | Voice mail system with personal assistant provisioning |
DE19841541B4 (en) | 1998-09-11 | 2007-12-06 | Püllen, Rainer | Subscriber unit for a multimedia service |
US6266637B1 (en) | 1998-09-11 | 2001-07-24 | International Business Machines Corporation | Phrase splicing and variable substitution using a trainable speech synthesizer |
US6317831B1 (en) | 1998-09-21 | 2001-11-13 | Openwave Systems Inc. | Method and apparatus for establishing a secure connection over a one-way data path |
US6275824B1 (en) | 1998-10-02 | 2001-08-14 | Ncr Corporation | System and method for managing data privacy in a database management system |
IL140805A0 (en) | 1998-10-02 | 2002-02-10 | Ibm | Structure skeletons for efficient voice navigation through generic hierarchical objects |
GB9821969D0 (en) | 1998-10-08 | 1998-12-02 | Canon Kk | Apparatus and method for processing natural language |
US6928614B1 (en) | 1998-10-13 | 2005-08-09 | Visteon Global Technologies, Inc. | Mobile office with speech recognition |
US6453292B2 (en) | 1998-10-28 | 2002-09-17 | International Business Machines Corporation | Command boundary identifier for conversational natural language |
US6208971B1 (en) | 1998-10-30 | 2001-03-27 | Apple Computer, Inc. | Method and apparatus for command recognition using data-driven semantic inference |
US6321092B1 (en) | 1998-11-03 | 2001-11-20 | Signal Soft Corporation | Multiple input data management for wireless location-based applications |
US6446076B1 (en) | 1998-11-12 | 2002-09-03 | Accenture Llp. | Voice interactive web-based agent system responsive to a user location for prioritizing and formatting information |
JP2002530703A (en) | 1998-11-13 | 2002-09-17 | ルノー・アンド・オスピー・スピーチ・プロダクツ・ナームローゼ・ベンノートシャープ | Speech synthesis using concatenation of speech waveforms |
US6606599B2 (en) | 1998-12-23 | 2003-08-12 | Interactive Speech Technologies, Llc | Method for integrating computing processes with an interface controlled by voice actuated grammars |
US6246981B1 (en) | 1998-11-25 | 2001-06-12 | International Business Machines Corporation | Natural language task-oriented dialog manager and method |
US7082397B2 (en) | 1998-12-01 | 2006-07-25 | Nuance Communications, Inc. | System for and method of creating and browsing a voice web |
US6260024B1 (en) | 1998-12-02 | 2001-07-10 | Gary Shkedy | Method and apparatus for facilitating buyer-driven purchase orders on a commercial network system |
US7881936B2 (en) | 1998-12-04 | 2011-02-01 | Tegic Communications, Inc. | Multimodal disambiguation of speech recognition |
US6317707B1 (en) | 1998-12-07 | 2001-11-13 | At&T Corp. | Automatic clustering of tokens from a corpus for grammar acquisition |
US6308149B1 (en) | 1998-12-16 | 2001-10-23 | Xerox Corporation | Grouping words with equivalent substrings by automatic clustering based on suffix relationships |
US6523172B1 (en) | 1998-12-17 | 2003-02-18 | Evolutionary Technologies International, Inc. | Parser translator system and method |
US6460029B1 (en) | 1998-12-23 | 2002-10-01 | Microsoft Corporation | System for improving search text |
US7036128B1 (en) | 1999-01-05 | 2006-04-25 | Sri International Offices | Using a community of distributed electronic agents to support a highly mobile, ambient computing environment |
US6742021B1 (en) | 1999-01-05 | 2004-05-25 | Sri International, Inc. | Navigating network-based electronic information using spoken input with multimodal error feedback |
US6851115B1 (en) | 1999-01-05 | 2005-02-01 | Sri International | Software-based architecture for communication and cooperation among distributed electronic agents |
US6757718B1 (en) | 1999-01-05 | 2004-06-29 | Sri International | Mobile navigation of network-based electronic information using spoken input |
US6513063B1 (en) | 1999-01-05 | 2003-01-28 | Sri International | Accessing network-based electronic information through scripted online interfaces using spoken input |
US6523061B1 (en) | 1999-01-05 | 2003-02-18 | Sri International, Inc. | System, method, and article of manufacture for agent-based navigation in a speech-based data navigation system |
US7152070B1 (en) | 1999-01-08 | 2006-12-19 | The Regents Of The University Of California | System and method for integrating and accessing multiple data sources within a data warehouse architecture |
US6505183B1 (en) | 1999-02-04 | 2003-01-07 | Authoria, Inc. | Human resource knowledge modeling and delivery system |
US6317718B1 (en) | 1999-02-26 | 2001-11-13 | Accenture Properties (2) B.V. | System, method and article of manufacture for location-based filtering for shopping agent in the physical world |
GB9904662D0 (en) | 1999-03-01 | 1999-04-21 | Canon Kk | Natural language search method and apparatus |
US6356905B1 (en) | 1999-03-05 | 2002-03-12 | Accenture Llp | System, method and article of manufacture for mobile communication utilizing an interface support framework |
US6928404B1 (en) | 1999-03-17 | 2005-08-09 | International Business Machines Corporation | System and methods for acoustic and language modeling for automatic speech recognition with large vocabularies |
US6584464B1 (en) | 1999-03-19 | 2003-06-24 | Ask Jeeves, Inc. | Grammar template query system |
EP1088299A2 (en) | 1999-03-26 | 2001-04-04 | Scansoft, Inc. | Client-server speech recognition |
US6356854B1 (en) | 1999-04-05 | 2002-03-12 | Delphi Technologies, Inc. | Holographic object position and type sensing system and method |
US6631346B1 (en) | 1999-04-07 | 2003-10-07 | Matsushita Electric Industrial Co., Ltd. | Method and apparatus for natural language parsing using multiple passes and tags |
WO2000060435A2 (en) | 1999-04-07 | 2000-10-12 | Rensselaer Polytechnic Institute | System and method for accessing personal information |
US6647260B2 (en) | 1999-04-09 | 2003-11-11 | Openwave Systems Inc. | Method and system facilitating web based provisioning of two-way mobile communications devices |
US6924828B1 (en) | 1999-04-27 | 2005-08-02 | Surfnotes | Method and apparatus for improved information representation |
US6697780B1 (en) | 1999-04-30 | 2004-02-24 | At&T Corp. | Method and apparatus for rapid acoustic unit selection from a large speech corpus |
US20020032564A1 (en) | 2000-04-19 | 2002-03-14 | Farzad Ehsani | Phrase-based dialogue modeling with particular application to creating a recognition grammar for a voice-controlled user interface |
JP2003505778A (en) | 1999-05-28 | 2003-02-12 | セーダ インコーポレイテッド | Phrase-based dialogue modeling with specific use in creating recognition grammars for voice control user interfaces |
US6931384B1 (en) | 1999-06-04 | 2005-08-16 | Microsoft Corporation | System and method providing utility-based decision making about clarification dialog given communicative uncertainty |
US6598039B1 (en) | 1999-06-08 | 2003-07-22 | Albert-Inc. S.A. | Natural language interface for searching database |
US6615175B1 (en) | 1999-06-10 | 2003-09-02 | Robert F. Gazdzinski | “Smart” elevator system and method |
US8065155B1 (en) | 1999-06-10 | 2011-11-22 | Gazdzinski Robert F | Adaptive advertising apparatus and methods |
US7711565B1 (en) | 1999-06-10 | 2010-05-04 | Gazdzinski Robert F | “Smart” elevator system and method |
US7093693B1 (en) | 1999-06-10 | 2006-08-22 | Gazdzinski Robert F | Elevator access control system and method |
US6711585B1 (en) | 1999-06-15 | 2004-03-23 | Kanisa Inc. | System and method for implementing a knowledge management system |
JP3361291B2 (en) | 1999-07-23 | 2003-01-07 | コナミ株式会社 | Speech synthesis method, speech synthesis device, and computer-readable medium recording speech synthesis program |
US6421672B1 (en) | 1999-07-27 | 2002-07-16 | Verizon Services Corp. | Apparatus for and method of disambiguation of directory listing searches utilizing multiple selectable secondary search keys |
EP1079387A3 (en) | 1999-08-26 | 2003-07-09 | Matsushita Electric Industrial Co., Ltd. | Mechanism for storing information about recorded television broadcasts |
US6697824B1 (en) | 1999-08-31 | 2004-02-24 | Accenture Llp | Relationship management in an E-commerce application framework |
US6601234B1 (en) | 1999-08-31 | 2003-07-29 | Accenture Llp | Attribute dictionary in a business logic services environment |
US6912499B1 (en) | 1999-08-31 | 2005-06-28 | Nortel Networks Limited | Method and apparatus for training a multilingual speech model set |
US7127403B1 (en) | 1999-09-13 | 2006-10-24 | Microstrategy, Inc. | System and method for personalizing an interactive voice broadcast of a voice service based on particulars of a request |
US6601026B2 (en) | 1999-09-17 | 2003-07-29 | Discern Communications, Inc. | Information retrieval by natural language querying |
US6625583B1 (en) | 1999-10-06 | 2003-09-23 | Goldman, Sachs & Co. | Handheld trading system interface |
US6505175B1 (en) | 1999-10-06 | 2003-01-07 | Goldman, Sachs & Co. | Order centric tracking system |
US7020685B1 (en) | 1999-10-08 | 2006-03-28 | Openwave Systems Inc. | Method and apparatus for providing internet content to SMS-based wireless devices |
AU8030300A (en) | 1999-10-19 | 2001-04-30 | Sony Electronics Inc. | Natural language interface control system |
US6807574B1 (en) | 1999-10-22 | 2004-10-19 | Tellme Networks, Inc. | Method and apparatus for content personalization over a telephone interface |
JP2001125896A (en) | 1999-10-26 | 2001-05-11 | Victor Co Of Japan Ltd | Natural language interactive system |
US7310600B1 (en) | 1999-10-28 | 2007-12-18 | Canon Kabushiki Kaisha | Language recognition using a similarity measure |
US7392185B2 (en) | 1999-11-12 | 2008-06-24 | Phoenix Solutions, Inc. | Speech based learning/training system using semantic decoding |
US7725307B2 (en) | 1999-11-12 | 2010-05-25 | Phoenix Solutions, Inc. | Query engine for processing voice based queries including semantic decoding |
US7050977B1 (en) | 1999-11-12 | 2006-05-23 | Phoenix Solutions, Inc. | Speech-enabled server for internet website and method |
US6615172B1 (en) | 1999-11-12 | 2003-09-02 | Phoenix Solutions, Inc. | Intelligent query engine for processing voice based queries |
US9076448B2 (en) | 1999-11-12 | 2015-07-07 | Nuance Communications, Inc. | Distributed real time speech recognition system |
US6633846B1 (en) | 1999-11-12 | 2003-10-14 | Phoenix Solutions, Inc. | Distributed realtime speech recognition system |
US6665640B1 (en) | 1999-11-12 | 2003-12-16 | Phoenix Solutions, Inc. | Interactive speech based learning/training system formulating search queries based on natural language parsing of recognized user queries |
US6532446B1 (en) | 1999-11-24 | 2003-03-11 | Openwave Systems Inc. | Server based speech recognition user interface for wireless devices |
US6526382B1 (en) * | 1999-12-07 | 2003-02-25 | Comverse, Inc. | Language-oriented user interfaces for voice activated services |
US6526395B1 (en) | 1999-12-31 | 2003-02-25 | Intel Corporation | Application of personality models and interaction with synthetic characters in a computing system |
US6556983B1 (en) | 2000-01-12 | 2003-04-29 | Microsoft Corporation | Methods and apparatus for finding semantic information, such as usage logs, similar to a query using a pattern lattice data space |
US6546388B1 (en) | 2000-01-14 | 2003-04-08 | International Business Machines Corporation | Metadata search results ranking system |
US6701294B1 (en) | 2000-01-19 | 2004-03-02 | Lucent Technologies, Inc. | User interface for translating natural language inquiries into database queries and data presentations |
US6829603B1 (en) | 2000-02-02 | 2004-12-07 | International Business Machines Corp. | System, method and program product for interactive natural dialog |
US6895558B1 (en) | 2000-02-11 | 2005-05-17 | Microsoft Corporation | Multi-access mode electronic personal assistant |
US6640098B1 (en) | 2000-02-14 | 2003-10-28 | Action Engine Corporation | System for obtaining service-related information for local interactive wireless devices |
EP1272912A2 (en) | 2000-02-25 | 2003-01-08 | Synquiry Technologies, Ltd | Conceptual factoring and unification of graphs representing semantic models |
US6895380B2 (en) | 2000-03-02 | 2005-05-17 | Electro Standards Laboratories | Voice actuation with contextual learning for intelligent machine control |
US6449620B1 (en) | 2000-03-02 | 2002-09-10 | Nimble Technology, Inc. | Method and apparatus for generating information pages using semi-structured data stored in a structured manner |
US6757362B1 (en) | 2000-03-06 | 2004-06-29 | Avaya Technology Corp. | Personal virtual assistant |
EP1275042A2 (en) | 2000-03-06 | 2003-01-15 | Kanisa Inc. | A system and method for providing an intelligent multi-step dialog with a user |
US6466654B1 (en) | 2000-03-06 | 2002-10-15 | Avaya Technology Corp. | Personal virtual assistant with semantic tagging |
US6477488B1 (en) | 2000-03-10 | 2002-11-05 | Apple Computer, Inc. | Method for dynamic context scope selection in hybrid n-gram+LSA language modeling |
US6615220B1 (en) | 2000-03-14 | 2003-09-02 | Oracle International Corporation | Method and mechanism for data consolidation |
US6510417B1 (en) | 2000-03-21 | 2003-01-21 | America Online, Inc. | System and method for voice access to internet-based information |
GB2366009B (en) | 2000-03-22 | 2004-07-21 | Canon Kk | Natural language machine interface |
JP3728172B2 (en) | 2000-03-31 | 2005-12-21 | キヤノン株式会社 | Speech synthesis method and apparatus |
US7177798B2 (en) | 2000-04-07 | 2007-02-13 | Rensselaer Polytechnic Institute | Natural language interface using constrained intermediate dictionary of results |
US6810379B1 (en) | 2000-04-24 | 2004-10-26 | Sensory, Inc. | Client/server architecture for text-to-speech synthesis |
US6684187B1 (en) | 2000-06-30 | 2004-01-27 | At&T Corp. | Method and system for preselection of suitable units for concatenative speech |
US6691111B2 (en) | 2000-06-30 | 2004-02-10 | Research In Motion Limited | System and method for implementing a natural language user interface |
US6505158B1 (en) | 2000-07-05 | 2003-01-07 | At&T Corp. | Synthesis-based pre-selection of suitable units for concatenative speech |
JP3949356B2 (en) | 2000-07-12 | 2007-07-25 | 三菱電機株式会社 | Spoken dialogue system |
US7139709B2 (en) | 2000-07-20 | 2006-11-21 | Microsoft Corporation | Middleware layer between speech related applications and engines |
JP2002041276A (en) | 2000-07-24 | 2002-02-08 | Sony Corp | Interactive operation-supporting system, interactive operation-supporting method and recording medium |
US20060143007A1 (en) | 2000-07-24 | 2006-06-29 | Koh V E | User interaction with voice information services |
US7092928B1 (en) | 2000-07-31 | 2006-08-15 | Quantum Leap Research, Inc. | Intelligent portal engine |
US6778951B1 (en) | 2000-08-09 | 2004-08-17 | Concerto Software, Inc. | Information retrieval method with natural language interface |
US6766320B1 (en) | 2000-08-24 | 2004-07-20 | Microsoft Corporation | Search engine with natural language-based robust parsing for user query and relevance feedback learning |
DE10042944C2 (en) | 2000-08-31 | 2003-03-13 | Siemens Ag | Grapheme-phoneme conversion |
WO2002023523A2 (en) | 2000-09-15 | 2002-03-21 | Lernout & Hauspie Speech Products N.V. | Fast waveform synchronization for concatenation and time-scale modification of speech |
WO2002027712A1 (en) | 2000-09-29 | 2002-04-04 | Professorq, Inc. | Natural-language voice-activated personal assistant |
US6832194B1 (en) | 2000-10-26 | 2004-12-14 | Sensory, Incorporated | Audio recognition peripheral system |
US7027974B1 (en) | 2000-10-27 | 2006-04-11 | Science Applications International Corporation | Ontology-based parser for natural language processing |
US7006969B2 (en) | 2000-11-02 | 2006-02-28 | At&T Corp. | System and method of pattern recognition in very high-dimensional space |
EP1346344A1 (en) | 2000-12-18 | 2003-09-24 | Koninklijke Philips Electronics N.V. | Store speech, select vocabulary to recognize word |
US6937986B2 (en) | 2000-12-28 | 2005-08-30 | Comverse, Inc. | Automatic dynamic speech recognition vocabulary based on external sources of information |
WO2002054239A2 (en) | 2000-12-29 | 2002-07-11 | General Electric Company | Method and system for identifying repeatedly malfunctioning equipment |
US7257537B2 (en) | 2001-01-12 | 2007-08-14 | International Business Machines Corporation | Method and apparatus for performing dialog management in a computer conversational interface |
US6964023B2 (en) | 2001-02-05 | 2005-11-08 | International Business Machines Corporation | System and method for multi-modal focus detection, referential ambiguity resolution and mood classification using multi-modal input |
US7290039B1 (en) | 2001-02-27 | 2007-10-30 | Microsoft Corporation | Intent based processing |
US6721728B2 (en) | 2001-03-02 | 2004-04-13 | The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration | System, method and apparatus for discovering phrases in a database |
EP1490790A2 (en) | 2001-03-13 | 2004-12-29 | Intelligate Ltd. | Dynamic natural language understanding |
US6996531B2 (en) | 2001-03-30 | 2006-02-07 | Comverse Ltd. | Automated database assistance using a telephone for a speech based or text based multimedia communication mode |
US6654740B2 (en) | 2001-05-08 | 2003-11-25 | Sunflare Co., Ltd. | Probabilistic information retrieval based on differential latent semantic space |
US7085722B2 (en) | 2001-05-14 | 2006-08-01 | Sony Computer Entertainment America Inc. | System and method for menu-driven voice control of characters in a game environment |
US6944594B2 (en) | 2001-05-30 | 2005-09-13 | Bellsouth Intellectual Property Corporation | Multi-context conversational environment system and method |
US20020194003A1 (en) | 2001-06-05 | 2002-12-19 | Mozer Todd F. | Client-server security system and method |
US20020198714A1 (en) | 2001-06-26 | 2002-12-26 | Guojun Zhou | Statistical spoken dialog system |
US7139722B2 (en) | 2001-06-27 | 2006-11-21 | Bellsouth Intellectual Property Corporation | Location and time sensitive wireless calendaring |
US6604059B2 (en) | 2001-07-10 | 2003-08-05 | Koninklijke Philips Electronics N.V. | Predictive calendar |
US7987151B2 (en) | 2001-08-10 | 2011-07-26 | General Dynamics Advanced Info Systems, Inc. | Apparatus and method for problem solving using intelligent agents |
US6813491B1 (en) | 2001-08-31 | 2004-11-02 | Openwave Systems Inc. | Method and apparatus for adapting settings of wireless communication devices in accordance with user proximity |
US7403938B2 (en) | 2001-09-24 | 2008-07-22 | Iac Search & Media, Inc. | Natural language query processing |
US6985865B1 (en) | 2001-09-26 | 2006-01-10 | Sprint Spectrum L.P. | Method and system for enhanced response to voice commands in a voice command platform |
US20050196732A1 (en) | 2001-09-26 | 2005-09-08 | Scientific Learning Corporation | Method and apparatus for automated training of language learning skills |
US6650735B2 (en) | 2001-09-27 | 2003-11-18 | Microsoft Corporation | Integrated voice access to a variety of personal information services |
US7324947B2 (en) | 2001-10-03 | 2008-01-29 | Promptu Systems Corporation | Global speech user interface |
US7167832B2 (en) | 2001-10-15 | 2007-01-23 | At&T Corp. | Method for dialog management |
GB2381409B (en) | 2001-10-27 | 2004-04-28 | Hewlett Packard Ltd | Asynchronous access to synchronous voice services |
NO316480B1 (en) | 2001-11-15 | 2004-01-26 | Forinnova As | Method and system for textual examination and discovery |
US20030101054A1 (en) | 2001-11-27 | 2003-05-29 | Ncc, Llc | Integrated system and method for electronic speech recognition and transcription |
TW541517B (en) | 2001-12-25 | 2003-07-11 | Univ Nat Cheng Kung | Speech recognition system |
US7197460B1 (en) | 2002-04-23 | 2007-03-27 | At&T Corp. | System for handling frequently asked questions in a natural language dialog service |
US6847966B1 (en) | 2002-04-24 | 2005-01-25 | Engenium Corporation | Method and system for optimally searching a document database using a representative semantic space |
US7546382B2 (en) | 2002-05-28 | 2009-06-09 | International Business Machines Corporation | Methods and systems for authoring of mixed-initiative multi-modal interactions and related browsing mechanisms |
US7398209B2 (en) | 2002-06-03 | 2008-07-08 | Voicebox Technologies, Inc. | Systems and methods for responding to natural language speech utterance |
US7233790B2 (en) | 2002-06-28 | 2007-06-19 | Openwave Systems, Inc. | Device capability based discovery, packaging and provisioning of content for wireless mobile devices |
US7299033B2 (en) | 2002-06-28 | 2007-11-20 | Openwave Systems Inc. | Domain-based management of distribution of digital content from multiple suppliers to multiple wireless services subscribers |
US7693720B2 (en) | 2002-07-15 | 2010-04-06 | Voicebox Technologies, Inc. | Mobile systems and methods for responding to natural language speech utterance |
US7467087B1 (en) | 2002-10-10 | 2008-12-16 | Gillick Laurence S | Training and using pronunciation guessers in speech recognition |
WO2004049306A1 (en) | 2002-11-22 | 2004-06-10 | Roy Rosser | Autonomous response engine |
EP2017828A1 (en) | 2002-12-10 | 2009-01-21 | Kirusa, Inc. | Techniques for disambiguating speech input using multimodal interfaces |
US7386449B2 (en) | 2002-12-11 | 2008-06-10 | Voice Enabling Systems Technology Inc. | Knowledge-based flexible natural speech dialogue system |
US7956766B2 (en) | 2003-01-06 | 2011-06-07 | Panasonic Corporation | Apparatus operating system |
US7529671B2 (en) | 2003-03-04 | 2009-05-05 | Microsoft Corporation | Block synchronous decoding |
US6980949B2 (en) | 2003-03-14 | 2005-12-27 | Sonum Technologies, Inc. | Natural language processor |
US7496498B2 (en) | 2003-03-24 | 2009-02-24 | Microsoft Corporation | Front-end architecture for a multi-lingual text-to-speech system |
US7421393B1 (en) | 2004-03-01 | 2008-09-02 | At&T Corp. | System for developing a dialog manager using modular spoken-dialog components |
US7200559B2 (en) | 2003-05-29 | 2007-04-03 | Microsoft Corporation | Semantic object synchronous understanding implemented with speech application language tags |
US7720683B1 (en) | 2003-06-13 | 2010-05-18 | Sensory, Inc. | Method and apparatus of specifying and performing speech recognition operations |
US7475010B2 (en) | 2003-09-03 | 2009-01-06 | Lingospot, Inc. | Adaptive and scalable method for resolving natural language ambiguities |
US7418392B1 (en) | 2003-09-25 | 2008-08-26 | Sensory, Inc. | System and method for controlling the operation of a device by voice commands |
US7155706B2 (en) | 2003-10-24 | 2006-12-26 | Microsoft Corporation | Administrative tool environment |
US7584092B2 (en) | 2004-11-15 | 2009-09-01 | Microsoft Corporation | Unsupervised learning of paraphrase/translation alternations and selective application thereof |
US7412385B2 (en) | 2003-11-12 | 2008-08-12 | Microsoft Corporation | System for identifying paraphrases using machine translation |
US7447630B2 (en) | 2003-11-26 | 2008-11-04 | Microsoft Corporation | Method and apparatus for multi-sensory speech enhancement |
DE602004016681D1 (en) | 2003-12-05 | 2008-10-30 | Kenwood Corp | AUDIO DEVICE CONTROL DEVICE, AUDIO DEVICE CONTROL METHOD AND PROGRAM |
ES2312851T3 (en) | 2003-12-16 | 2009-03-01 | Loquendo Spa | VOICE TEXT PROCEDURE AND SYSTEM AND THE ASSOCIATED INFORMATIC PROGRAM. |
US7427024B1 (en) | 2003-12-17 | 2008-09-23 | Gazdzinski Mark J | Chattel management apparatus and methods |
US7552055B2 (en) | 2004-01-10 | 2009-06-23 | Microsoft Corporation | Dialog component re-use in recognition systems |
WO2005071663A2 (en) | 2004-01-16 | 2005-08-04 | Scansoft, Inc. | Corpus-based speech synthesis based on segment recombination |
US20050165607A1 (en) | 2004-01-22 | 2005-07-28 | At&T Corp. | System and method to disambiguate and clarify user intention in a spoken dialog system |
DE602004017955D1 (en) | 2004-01-29 | 2009-01-08 | Daimler Ag | Method and system for voice dialogue interface |
KR100462292B1 (en) | 2004-02-26 | 2004-12-17 | 엔에이치엔(주) | A method for providing search results list based on importance information and a system thereof |
US7693715B2 (en) | 2004-03-10 | 2010-04-06 | Microsoft Corporation | Generating large units of graphonemes with mutual information criterion for letter to sound conversion |
US7409337B1 (en) | 2004-03-30 | 2008-08-05 | Microsoft Corporation | Natural language processing interface |
US7496512B2 (en) | 2004-04-13 | 2009-02-24 | Microsoft Corporation | Refining of segmental boundaries in speech waveforms using contextual-dependent models |
US8095364B2 (en) | 2004-06-02 | 2012-01-10 | Tegic Communications, Inc. | Multimodal disambiguation of speech recognition |
US7720674B2 (en) | 2004-06-29 | 2010-05-18 | Sap Ag | Systems and methods for processing natural language queries |
TWI252049B (en) | 2004-07-23 | 2006-03-21 | Inventec Corp | Sound control system and method |
US7725318B2 (en) | 2004-07-30 | 2010-05-25 | Nice Systems Inc. | System and method for improving the accuracy of audio searching |
US7853574B2 (en) | 2004-08-26 | 2010-12-14 | International Business Machines Corporation | Method of generating a context-inferenced search query and of sorting a result of the query |
US7716056B2 (en) | 2004-09-27 | 2010-05-11 | Robert Bosch Corporation | Method and system for interactive conversational dialogue for cognitively overloaded device users |
US8107401B2 (en) | 2004-09-30 | 2012-01-31 | Avaya Inc. | Method and apparatus for providing a virtual assistant to a communication participant |
US7552046B2 (en) | 2004-11-15 | 2009-06-23 | Microsoft Corporation | Unsupervised learning of paraphrase/translation alternations and selective application thereof |
US7546235B2 (en) | 2004-11-15 | 2009-06-09 | Microsoft Corporation | Unsupervised learning of paraphrase/translation alternations and selective application thereof |
US7702500B2 (en) | 2004-11-24 | 2010-04-20 | Blaedow Karen R | Method and apparatus for determining the meaning of natural language |
CN1609859A (en) | 2004-11-26 | 2005-04-27 | 孙斌 | Search result clustering method |
US7376645B2 (en) | 2004-11-29 | 2008-05-20 | The Intellection Group, Inc. | Multimodal natural language query system and architecture for processing voice and proximity-based queries |
US8214214B2 (en) | 2004-12-03 | 2012-07-03 | Phoenix Solutions, Inc. | Emotion detection device and method for use in distributed systems |
US20060122834A1 (en) | 2004-12-03 | 2006-06-08 | Bennett Ian M | Emotion detection device & method for use in distributed systems |
US7636657B2 (en) | 2004-12-09 | 2009-12-22 | Microsoft Corporation | Method and apparatus for automatic grammar generation from data entries |
US7873654B2 (en) | 2005-01-24 | 2011-01-18 | The Intellection Group, Inc. | Multimodal natural language query system for processing and analyzing voice and proximity-based queries |
US7508373B2 (en) | 2005-01-28 | 2009-03-24 | Microsoft Corporation | Form factor and input method for language input |
GB0502259D0 (en) | 2005-02-03 | 2005-03-09 | British Telecomm | Document searching tool and method |
US7676026B1 (en) | 2005-03-08 | 2010-03-09 | Baxtech Asia Pte Ltd | Desktop telephony system |
US7925525B2 (en) | 2005-03-25 | 2011-04-12 | Microsoft Corporation | Smart reminders |
WO2006129967A1 (en) | 2005-05-30 | 2006-12-07 | Daumsoft, Inc. | Conversation system and method using conversational agent |
US8041570B2 (en) | 2005-05-31 | 2011-10-18 | Robert Bosch Corporation | Dialogue management using scripts |
US8024195B2 (en) | 2005-06-27 | 2011-09-20 | Sensory, Inc. | Systems and methods of performing speech recognition using historical information |
US7826945B2 (en) | 2005-07-01 | 2010-11-02 | You Zhang | Automobile speech-recognition interface |
WO2007019480A2 (en) | 2005-08-05 | 2007-02-15 | Realnetworks, Inc. | System and computer program product for chronologically presenting data |
US7640160B2 (en) | 2005-08-05 | 2009-12-29 | Voicebox Technologies, Inc. | Systems and methods for responding to natural language speech utterance |
US7620549B2 (en) | 2005-08-10 | 2009-11-17 | Voicebox Technologies, Inc. | System and method of supporting adaptive misrecognition in conversational speech |
US7949529B2 (en) | 2005-08-29 | 2011-05-24 | Voicebox Technologies, Inc. | Mobile systems and methods of supporting natural language human-machine interactions |
US8265939B2 (en) | 2005-08-31 | 2012-09-11 | Nuance Communications, Inc. | Hierarchical methods and apparatus for extracting user intent from spoken utterances |
US7634409B2 (en) | 2005-08-31 | 2009-12-15 | Voicebox Technologies, Inc. | Dynamic speech sharpening |
US8677377B2 (en) | 2005-09-08 | 2014-03-18 | Apple Inc. | Method and apparatus for building an intelligent automated assistant |
JP4908094B2 (en) | 2005-09-30 | 2012-04-04 | 株式会社リコー | Information processing system, information processing method, and information processing program |
US7930168B2 (en) | 2005-10-04 | 2011-04-19 | Robert Bosch Gmbh | Natural language processing of disfluent sentences |
US8620667B2 (en) | 2005-10-17 | 2013-12-31 | Microsoft Corporation | Flexible speech-activated command and control |
US7707032B2 (en) | 2005-10-20 | 2010-04-27 | National Cheng Kung University | Method and system for matching speech data |
US20070106674A1 (en) | 2005-11-10 | 2007-05-10 | Purusharth Agrawal | Field sales process facilitation systems and methods |
US7822749B2 (en) | 2005-11-28 | 2010-10-26 | Commvault Systems, Inc. | Systems and methods for classifying and transferring information in a storage network |
KR100810500B1 (en) | 2005-12-08 | 2008-03-07 | 한국전자통신연구원 | Method for enhancing usability in a spoken dialog system |
DE102005061365A1 (en) | 2005-12-21 | 2007-06-28 | Siemens Ag | Background applications e.g. home banking system, controlling method for use over e.g. user interface, involves associating transactions and transaction parameters over universal dialog specification, and universally operating applications |
US7996228B2 (en) | 2005-12-22 | 2011-08-09 | Microsoft Corporation | Voice initiated network operations |
US7599918B2 (en) | 2005-12-29 | 2009-10-06 | Microsoft Corporation | Dynamic search with implicit user intention mining |
JP2007183864A (en) | 2006-01-10 | 2007-07-19 | Fujitsu Ltd | File retrieval method and system therefor |
US20070174188A1 (en) | 2006-01-25 | 2007-07-26 | Fish Robert D | Electronic marketplace that facilitates transactions between consolidated buyers and/or sellers |
IL174107A0 (en) | 2006-02-01 | 2006-08-01 | Grois Dan | Method and system for advertising by means of a search engine over a data network |
KR100764174B1 (en) | 2006-03-03 | 2007-10-08 | 삼성전자주식회사 | Apparatus for providing voice dialogue service and method for operating the apparatus |
US7752152B2 (en) | 2006-03-17 | 2010-07-06 | Microsoft Corporation | Using predictive user models for language modeling on a personal device with user behavior models based on statistical modeling |
JP4734155B2 (en) | 2006-03-24 | 2011-07-27 | 株式会社東芝 | Speech recognition apparatus, speech recognition method, and speech recognition program |
US7707027B2 (en) | 2006-04-13 | 2010-04-27 | Nuance Communications, Inc. | Identification and rejection of meaningless input during natural language classification |
US8423347B2 (en) | 2006-06-06 | 2013-04-16 | Microsoft Corporation | Natural language personal information management |
US7523108B2 (en) | 2006-06-07 | 2009-04-21 | Platformation, Inc. | Methods and apparatus for searching with awareness of geography and languages |
US20100257160A1 (en) | 2006-06-07 | 2010-10-07 | Yu Cao | Methods & apparatus for searching with awareness of different types of information |
US7483894B2 (en) | 2006-06-07 | 2009-01-27 | Platformation Technologies, Inc | Methods and apparatus for entity search |
KR100776800B1 (en) | 2006-06-16 | 2007-11-19 | 한국전자통신연구원 | Method and system (apparatus) for user specific service using intelligent gadget |
US7548895B2 (en) | 2006-06-30 | 2009-06-16 | Microsoft Corporation | Communication-prompted user assistance |
US9318108B2 (en) | 2010-01-18 | 2016-04-19 | Apple Inc. | Intelligent automated assistant |
US20080077384A1 (en) * | 2006-09-22 | 2008-03-27 | International Business Machines Corporation | Dynamically translating a software application to a user selected target language that is not natively provided by the software application |
US8073681B2 (en) | 2006-10-16 | 2011-12-06 | Voicebox Technologies, Inc. | System and method for a cooperative conversational voice user interface |
US20080129520A1 (en) | 2006-12-01 | 2008-06-05 | Apple Computer, Inc. | Electronic device with enhanced audio feedback |
WO2008085742A2 (en) | 2007-01-07 | 2008-07-17 | Apple Inc. | Portable multifunction device, method and graphical user interface for interacting with user input elements in displayed content |
KR100883657B1 (en) | 2007-01-26 | 2009-02-18 | 삼성전자주식회사 | Method and apparatus for searching a music using speech recognition |
US7818176B2 (en) | 2007-02-06 | 2010-10-19 | Voicebox Technologies, Inc. | System and method for selecting and presenting advertisements based on natural language processing of voice-based input |
US7822608B2 (en) | 2007-02-27 | 2010-10-26 | Nuance Communications, Inc. | Disambiguating a speech recognition grammar in a multimodal application |
US20080221900A1 (en) | 2007-03-07 | 2008-09-11 | Cerra Joseph P | Mobile local search environment speech processing facility |
US7801729B2 (en) | 2007-03-13 | 2010-09-21 | Sensory, Inc. | Using multiple attributes to create a voice search playlist |
US8219406B2 (en) | 2007-03-15 | 2012-07-10 | Microsoft Corporation | Speech-centric multimodal user interface design in mobile technology |
US7809610B2 (en) | 2007-04-09 | 2010-10-05 | Platformation, Inc. | Methods and apparatus for freshness and completeness of information |
US7983915B2 (en) | 2007-04-30 | 2011-07-19 | Sonic Foundry, Inc. | Audio content search engine |
US8055708B2 (en) | 2007-06-01 | 2011-11-08 | Microsoft Corporation | Multimedia spaces |
US8204238B2 (en) | 2007-06-08 | 2012-06-19 | Sensory, Inc | Systems and methods of sonic communication |
US8190627B2 (en) | 2007-06-28 | 2012-05-29 | Microsoft Corporation | Machine assisted query formulation |
US8019606B2 (en) | 2007-06-29 | 2011-09-13 | Microsoft Corporation | Identification and selection of a software application via speech |
JP2009036999A (en) | 2007-08-01 | 2009-02-19 | Infocom Corp | Interactive method using computer, interactive system, computer program and computer-readable storage medium |
KR101359715B1 (en) | 2007-08-24 | 2014-02-10 | 삼성전자주식회사 | Method and apparatus for providing mobile voice web |
US8190359B2 (en) | 2007-08-31 | 2012-05-29 | Proxpro, Inc. | Situation-aware personal information management for a mobile device |
US20090058823A1 (en) | 2007-09-04 | 2009-03-05 | Apple Inc. | Virtual Keyboards in Multi-Language Environment |
US8838760B2 (en) | 2007-09-14 | 2014-09-16 | Ricoh Co., Ltd. | Workflow-enabled provider |
KR100920267B1 (en) | 2007-09-17 | 2009-10-05 | 한국전자통신연구원 | System for voice communication analysis and method thereof |
US8706476B2 (en) | 2007-09-18 | 2014-04-22 | Ariadne Genomics, Inc. | Natural language processing method by analyzing primitive sentences, logical clauses, clause types and verbal blocks |
US8165886B1 (en) | 2007-10-04 | 2012-04-24 | Great Northern Research LLC | Speech interface system and method for control and interaction with applications on a computing system |
US8036901B2 (en) | 2007-10-05 | 2011-10-11 | Sensory, Incorporated | Systems and methods of performing speech recognition using sensory inputs of human position |
US20090112677A1 (en) | 2007-10-24 | 2009-04-30 | Rhett Randolph L | Method for automatically developing suggested optimal work schedules from unsorted group and individual task lists |
US7840447B2 (en) | 2007-10-30 | 2010-11-23 | Leonard Kleinrock | Pricing and auctioning of bundled items among multiple sellers and buyers |
US7983997B2 (en) | 2007-11-02 | 2011-07-19 | Florida Institute For Human And Machine Cognition, Inc. | Interactive complex task teaching system that allows for natural language input, recognizes a user's intent, and automatically performs tasks in document object model (DOM) nodes |
US8112280B2 (en) | 2007-11-19 | 2012-02-07 | Sensory, Inc. | Systems and methods of performing speech recognition with barge-in for use in a bluetooth system |
US8140335B2 (en) | 2007-12-11 | 2012-03-20 | Voicebox Technologies, Inc. | System and method for providing a natural language voice user interface in an integrated voice navigation services environment |
US10002189B2 (en) | 2007-12-20 | 2018-06-19 | Apple Inc. | Method and apparatus for searching using an active ontology |
US8219407B1 (en) | 2007-12-27 | 2012-07-10 | Great Northern Research, LLC | Method for processing the output of a speech recognizer |
US8099289B2 (en) | 2008-02-13 | 2012-01-17 | Sensory, Inc. | Voice interface and search for electronic devices including bluetooth headsets and remote systems |
US8958848B2 (en) | 2008-04-08 | 2015-02-17 | Lg Electronics Inc. | Mobile terminal and menu control method thereof |
US8666824B2 (en) | 2008-04-23 | 2014-03-04 | Dell Products L.P. | Digital media content location and purchasing system |
US8249857B2 (en) * | 2008-04-24 | 2012-08-21 | International Business Machines Corporation | Multilingual administration of enterprise data with user selected target language translation |
US8594995B2 (en) * | 2008-04-24 | 2013-11-26 | Nuance Communications, Inc. | Multilingual asynchronous communications of speech messages recorded in digital media files |
US8285344B2 (en) | 2008-05-21 | 2012-10-09 | DP Technlogies, Inc. | Method and apparatus for adjusting audio for a user environment |
US8589161B2 (en) | 2008-05-27 | 2013-11-19 | Voicebox Technologies, Inc. | System and method for an integrated, multi-modal, multi-device natural language voice services environment |
US8694355B2 (en) | 2008-05-30 | 2014-04-08 | Sri International | Method and apparatus for automated assistance with task management |
US8423288B2 (en) | 2009-11-30 | 2013-04-16 | Apple Inc. | Dynamic alerts for calendar events |
US8166019B1 (en) | 2008-07-21 | 2012-04-24 | Sprint Communications Company L.P. | Providing suggested actions in response to textual communications |
US9200913B2 (en) | 2008-10-07 | 2015-12-01 | Telecommunication Systems, Inc. | User interface for predictive traffic |
US8140328B2 (en) | 2008-12-01 | 2012-03-20 | At&T Intellectual Property I, L.P. | User intention based on N-best list of recognition hypotheses for utterances in a dialog |
US8326637B2 (en) | 2009-02-20 | 2012-12-04 | Voicebox Technologies, Inc. | System and method for processing multi-modal device interactions in a natural language voice services environment |
US8805823B2 (en) | 2009-04-14 | 2014-08-12 | Sri International | Content processing systems and methods |
JP5911796B2 (en) | 2009-04-30 | 2016-04-27 | サムスン エレクトロニクス カンパニー リミテッド | User intention inference apparatus and method using multimodal information |
KR101581883B1 (en) | 2009-04-30 | 2016-01-11 | 삼성전자주식회사 | Appratus for detecting voice using motion information and method thereof |
US8498857B2 (en) * | 2009-05-19 | 2013-07-30 | Tata Consultancy Services Limited | System and method for rapid prototyping of existing speech recognition solutions in different languages |
US9858925B2 (en) | 2009-06-05 | 2018-01-02 | Apple Inc. | Using context information to facilitate processing of commands in a virtual assistant |
US10540976B2 (en) | 2009-06-05 | 2020-01-21 | Apple Inc. | Contextual voice commands |
US20120311585A1 (en) | 2011-06-03 | 2012-12-06 | Apple Inc. | Organizing task items that represent tasks to perform |
KR101562792B1 (en) | 2009-06-10 | 2015-10-23 | 삼성전자주식회사 | Apparatus and method for providing goal predictive interface |
US8527278B2 (en) | 2009-06-29 | 2013-09-03 | Abraham Ben David | Intelligent home automation |
US20110047072A1 (en) | 2009-08-07 | 2011-02-24 | Visa U.S.A. Inc. | Systems and Methods for Propensity Analysis and Validation |
US8768313B2 (en) | 2009-08-17 | 2014-07-01 | Digimarc Corporation | Methods and systems for image or audio recognition processing |
WO2011028842A2 (en) | 2009-09-02 | 2011-03-10 | Sri International | Method and apparatus for exploiting human feedback in an intelligent automated assistant |
US8321527B2 (en) | 2009-09-10 | 2012-11-27 | Tribal Brands | System and method for tracking user location and associated activity and responsively providing mobile device updates |
KR20110036385A (en) | 2009-10-01 | 2011-04-07 | 삼성전자주식회사 | Apparatus for analyzing intention of user and method thereof |
US20110099507A1 (en) | 2009-10-28 | 2011-04-28 | Google Inc. | Displaying a collection of interactive elements that trigger actions directed to an item |
US9197736B2 (en) | 2009-12-31 | 2015-11-24 | Digimarc Corporation | Intuitive computing methods and systems |
US20120137367A1 (en) | 2009-11-06 | 2012-05-31 | Cataphora, Inc. | Continuous anomaly detection based on behavior modeling and heterogeneous information analysis |
US9171541B2 (en) | 2009-11-10 | 2015-10-27 | Voicebox Technologies Corporation | System and method for hybrid processing in a natural language voice services environment |
WO2011059997A1 (en) | 2009-11-10 | 2011-05-19 | Voicebox Technologies, Inc. | System and method for providing a natural language content dedication service |
US8712759B2 (en) | 2009-11-13 | 2014-04-29 | Clausal Computing Oy | Specializing disambiguation of a natural language expression |
KR101960835B1 (en) | 2009-11-24 | 2019-03-21 | 삼성전자주식회사 | Schedule Management System Using Interactive Robot and Method Thereof |
US8396888B2 (en) | 2009-12-04 | 2013-03-12 | Google Inc. | Location-based searching using a search area that corresponds to a geographical location of a computing device |
KR101622111B1 (en) | 2009-12-11 | 2016-05-18 | 삼성전자 주식회사 | Dialog system and conversational method thereof |
US20110161309A1 (en) | 2009-12-29 | 2011-06-30 | Lx1 Technology Limited | Method Of Sorting The Result Set Of A Search Engine |
US8494852B2 (en) | 2010-01-05 | 2013-07-23 | Google Inc. | Word-level correction of speech input |
US8334842B2 (en) | 2010-01-15 | 2012-12-18 | Microsoft Corporation | Recognizing user intent in motion capture system |
US8626511B2 (en) | 2010-01-22 | 2014-01-07 | Google Inc. | Multi-dimensional disambiguation of voice commands |
US20110218855A1 (en) | 2010-03-03 | 2011-09-08 | Platformation, Inc. | Offering Promotions Based on Query Analysis |
US8265928B2 (en) | 2010-04-14 | 2012-09-11 | Google Inc. | Geotagged environmental audio for enhanced speech recognition accuracy |
US20110279368A1 (en) | 2010-05-12 | 2011-11-17 | Microsoft Corporation | Inferring user intent to engage a motion capture system |
US8694313B2 (en) | 2010-05-19 | 2014-04-08 | Google Inc. | Disambiguation of contact information using historical data |
US8522283B2 (en) | 2010-05-20 | 2013-08-27 | Google Inc. | Television remote control data transfer |
US8468012B2 (en) | 2010-05-26 | 2013-06-18 | Google Inc. | Acoustic model adaptation using geographic information |
US20110306426A1 (en) | 2010-06-10 | 2011-12-15 | Microsoft Corporation | Activity Participation Based On User Intent |
US8234111B2 (en) | 2010-06-14 | 2012-07-31 | Google Inc. | Speech and noise models for speech recognition |
US8411874B2 (en) | 2010-06-30 | 2013-04-02 | Google Inc. | Removing noise from audio |
US8775156B2 (en) | 2010-08-05 | 2014-07-08 | Google Inc. | Translating languages in response to device motion |
US8359020B2 (en) | 2010-08-06 | 2013-01-22 | Google Inc. | Automatically monitoring for voice input based on context |
US8473289B2 (en) | 2010-08-06 | 2013-06-25 | Google Inc. | Disambiguating input based on context |
EP2702473A1 (en) | 2011-04-25 | 2014-03-05 | Veveo, Inc. | System and method for an intelligent personal timeline assistant |
-
2011
- 2011-06-21 US US13/165,516 patent/US8812294B2/en not_active Expired - Fee Related
-
2012
- 2012-06-19 WO PCT/US2012/043100 patent/WO2012177607A1/en active Application Filing
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070239429A1 (en) * | 1998-09-25 | 2007-10-11 | Johnson Christopher S | Systems and methods for multiple mode voice and data communications using intelligently bridged TDM and packet buses and methods for implementing language capabilities using the same |
US20030101045A1 (en) * | 2001-11-29 | 2003-05-29 | Peter Moffatt | Method and apparatus for playing recordings of spoken alphanumeric characters |
Non-Patent Citations (3)
Title |
---|
AIKAWA T ET AL: "Generation for Multilingual MT", INTERNET CITATION, 18 September 2001 (2001-09-18), XP002385617, Retrieved from the Internet <URL:http://www.eamt.org/summitVIII/papers/aikawa.pdf> [retrieved on 20060615] * |
B JAWAID: "Machine Translation with Significant Word Reordering and Rich Target-Side Morphology", WDS'11 PROCEEDINGS OF CONTRIBUTED PAPERS, PART I, 31 May 2011 (2011-05-31), pages 161 - 166, XP055043227, Retrieved from the Internet <URL:http://ufal.mff.cuni.cz/~jawaid/publications/wds-2011.pdf> [retrieved on 20121106] * |
MARIANNE SANTAHOLMA: "Grammar sharing techniques for Rule-Based Multilingual NLP systems", PROCEEDINGS OF THE 16TH NORDIC CONFERENCE OF COMPUTATIONAL LINGUISTICS NODALIDA-2007, 25 May 2007 (2007-05-25), Tartu, ESTONIA, pages 253 - 260, XP055043195, Retrieved from the Internet <URL:http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.95.7016&rep=rep1&type=pdf> [retrieved on 20121106] * |
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