Patents by Inventor Rajesh Balchandran
Rajesh Balchandran has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 10192543Abstract: A method (300) and system (100) is provided to add the creation of examples at a developer level in the generation of Natural Language Understanding (NLU) models, tying the examples into a NLU sentence database (130), automatically validating (310) a correct outcome of using the examples, and automatically resolving (316) problems the user has using the examples. The method (300) can convey examples of what a caller can say to a Natural Language Understanding (NLU) application. The method includes entering at least one example associated with an existing routing destination, and ensuring an NLU model correctly interprets the example unambiguously for correctly routing a call to the routing destination. The method can include presenting the example sentence in a help message (126) within an NLU dialogue as an example of what a caller can say for connecting the caller to a desired routing destination.Type: GrantFiled: May 10, 2016Date of Patent: January 29, 2019Assignee: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda M. Boyer, James R. Lewis, Brent D. Metz
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Patent number: 9767092Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: GrantFiled: August 15, 2016Date of Patent: September 19, 2017Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20160350281Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: ApplicationFiled: August 15, 2016Publication date: December 1, 2016Inventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Patent number: 9454525Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: GrantFiled: May 20, 2013Date of Patent: September 27, 2016Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20160253991Abstract: A method (300) and system (100) is provided to add the creation of examples at a developer level in the generation of Natural Language Understanding (NLU) models, tying the examples into a NLU sentence database (130), automatically validating (310) a correct outcome of using the examples, and automatically resolving (316) problems the user has using the examples. The method (300) can convey examples of what a caller can say to a Natural Language Understanding (NLU) application. The method includes entering at least one example associated with an existing routing destination, and ensuring an NLU model correctly interprets the example unambiguously for correctly routing a call to the routing destination. The method can include presenting the example sentence in a help message (126) within an NLU dialogue as an example of what a caller can say for connecting the caller to a desired routing destination.Type: ApplicationFiled: May 10, 2016Publication date: September 1, 2016Applicant: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda M. Boyer, James R. Lewis, Brent D. Metz
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Patent number: 9384190Abstract: A method (300) and system (100) is provided to add the creation of examples at a developer level in the generation of Natural Language Understanding (NLU) models, tying the examples into a NLU sentence database (130), automatically validating (310) a correct outcome of using the examples, and automatically resolving (316) problems the user has using the examples. The method (300) can convey examples of what a caller can say to a Natural Language Understanding (NLU) application. The method includes entering at least one example associated with an existing routing destination, and ensuring an NLU model correctly interprets the example unambiguously for correctly routing a can to the routing destination. The method can include presenting the example sentence in a help message (126) within an NLU dialog as an example of what a caller can say for connecting the caller to a desired routing destination.Type: GrantFiled: November 25, 2013Date of Patent: July 5, 2016Assignee: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda M. Boyer, James R. Lewis, Brent D. Metz
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Patent number: 9342588Abstract: A method of creating a statistical classification model for a classifier within a natural language understanding system can include processing training data using an existing statistical classification model. Sentences of the training data correctly classified into a selected class of the statistical classification model can be selected. The selected sentences of the training data can be assigned to a fringe group or a core group according to confidence score. The training data can be updated by associating the fringe group with a fringe subclass of the selected class and the core group with a core subclass of the selected class. A new statistical classification model can be built from the updated training data. The new statistical classification model can be output.Type: GrantFiled: June 18, 2007Date of Patent: May 17, 2016Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Patent number: 9104287Abstract: A method for collecting data for statistical modeling purposes can include the step of selecting at least one user interface type from a plurality of previously defined user interface types. Parameters of the selected interface type can be defined for a particular data collection instance. Target participant data can be inputted. A data collection interface based upon the selected interface type and defined parameters can be deployed. Messages can be automatically conveyed to data providers selected in accordance with the target participant data. The data providers can be permitted to access the deployed data collection interface. Data provided by the data providers can be automatically stored and used for statistical modeling purposes related to the data collection instance.Type: GrantFiled: October 27, 2005Date of Patent: August 11, 2015Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Ilya Skuratovsky
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Patent number: 9058319Abstract: A method of classifying text input for use with a natural language understanding system can include determining classification information including a primary classification and one or more secondary classifications for a received text input using a statistical classification model (statistical model). A statistical classification sub-model (statistical sub-model) can be selectively built according to a model generation criterion applied to the classification information. The method further can include selecting the primary classification or the secondary classification for the text input as a final classification according to the statistical sub-model and outputting the final classification for the text input.Type: GrantFiled: June 18, 2007Date of Patent: June 16, 2015Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20140156265Abstract: A method (300) and system (100) is provided to add the creation of examples at a developer level in the generation of Natural Language Understanding (NLU) models, tying the examples into a NLU sentence database (130), automatically validating (310) a correct outcome of using the examples, and automatically resolving (316) problems the user has using the examples. The method (300) can convey examples of what a caller can say to a Natural Language Understanding (NLU) application. The method includes entering at least one example associated with an existing routing destination, and ensuring an NLU model correctly interprets the example unambiguously for correctly routing a can to the routing destination. The method can include presenting the example sentence in a help message (126) within an NLU dialogue as an example of what a caller can say for connecting the caller to a desired routing destination.Type: ApplicationFiled: November 25, 2013Publication date: June 5, 2014Applicant: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda M. Boyer, James R. Lewis, Brent D. Metz
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Patent number: 8630856Abstract: A method for processing language input can include the step of determining at least two possible meanings for a language input. For each possible meaning, a probability that the possible meaning is a correct interpretation of the language input can be determined. At least one relative data computation can be computed based at least in part upon the probabilities. At least one irregularity within the language input can be detected based upon the relative delta computation. The irregularity can include mumble, ambiguous input, and/or compound input. At least one programmatic action can be performed responsive to the detection of the irregularity.Type: GrantFiled: July 8, 2009Date of Patent: January 14, 2014Assignee: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda M. Boyer
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Patent number: 8612229Abstract: A method (300) and system (100) is provided to add the creation of examples at a developer level in the generation of Natural Language Understanding (NLU) models, tying the examples into a NLU sentence database (130), automatically validating (310) a correct outcome of using the examples, and automatically resolving (316) problems the user has using the examples. The method (300) can convey examples of what a caller can say to a Natural Language Understanding (NLU) application. The method includes entering at least one example associated with an existing routing destination, and ensuring an NLU model correctly interprets the example unambiguously for correctly routing a call to the routing destination. The method can include presenting the example sentence in a help message (126) within an NLU dialogue as an example of what a caller can say for connecting the caller to a desired routing destination.Type: GrantFiled: December 15, 2005Date of Patent: December 17, 2013Assignee: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda M. Boyer, James R. Lewis, Brent D. Metz
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Publication number: 20130262093Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: ApplicationFiled: May 20, 2013Publication date: October 3, 2013Applicant: International Business Machines CorporationInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Patent number: 8521511Abstract: A method of extracting information from text within a natural language understanding system can include processing a text input through at least one statistical model for each of a plurality of features to be extracted from the text input. For each feature, at least one value can be determined, at least in part, using the statistical model associated with the feature. One value for each feature can be combined to create a complex information target. The complex information target can be output.Type: GrantFiled: June 18, 2007Date of Patent: August 27, 2013Assignee: International Business Machines CorporationInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Publication number: 20130086059Abstract: A method of automatically processing text data is described. An initial set of data tags is developed that characterize text data in a text database. Higher order entities are determined which are characteristic of patterns in the data tags. Then the text data is automatically tagged based on the higher order entities.Type: ApplicationFiled: October 3, 2011Publication date: April 4, 2013Applicant: NUANCE COMMUNICATIONS, INC.Inventors: Rajesh Balchandran, Leonid Rachevsky, Bhuvana Ramabhadran
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Patent number: 8285539Abstract: A method of processing text within a natural language understanding system can include applying a first tokenization technique to a sentence using a statistical tokenization model. A second tokenization technique using a named entity can be applied to the sentence when the first tokenization technique does not extract a needed token according to a class of the sentence. A token determined according to at least one of the tokenization techniques can be output.Type: GrantFiled: June 18, 2007Date of Patent: October 9, 2012Assignee: International Business Machines CorporationInventors: Rajesh Balchandran, Linda M. Boyer, Gregory Purdy
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Patent number: 7974835Abstract: In a natural language, mixed-initiative system, a method of processing user dialogue can include receiving a user input and determining whether the user input specifies an action to be performed or a token of an action. The user input can be selectively routed to an action interpreter or a token interpreter according to the determining step.Type: GrantFiled: April 30, 2008Date of Patent: July 5, 2011Assignee: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda Boyer
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Patent number: 7835911Abstract: The invention disclosed herein concerns a system (100) and method (600) for building a language model representation of an NLU application. The method 500 can include categorizing an NLU application domain (602), classifying a corpus in view of the categorization (604), and training at least one language model in view of the classification (606). The categorization produces a hierarchical tree of categories, sub-categories and end targets across one or more features for interpreting one or more natural language input requests. During development of an NLU application, a developer assigns sentences of the NLU application to categories, sub-categories or end targets across one or more features for associating each sentence with desire interpretations.Type: GrantFiled: December 30, 2005Date of Patent: November 16, 2010Assignee: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda M. Boyer
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Patent number: 7707027Abstract: A method for identifying data that is meaningless and generating a natural language statistical model which can reject meaningless input. The method can include identifying unigrams that are individually meaningless from a set of training data. At least a portion of the unigrams identified as being meaningless can be assigned to a first n-gram class. The method also can include identifying bigrams that are entirely composed of meaningless unigrams and determining whether the identified bigrams are individually meaningless. At least a portion of the bigrams identified as being individually meaningless can be assigned to the first n-gram class.Type: GrantFiled: April 13, 2006Date of Patent: April 27, 2010Assignee: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda Boyer
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Publication number: 20100010805Abstract: A method for processing language input can include the step of determining at least two possible meanings for a language input. For each possible meaning, a probability that the possible meaning is a correct interpretation of the language input can be determined. At least one relative data computation can be computed based at least in part upon the probabilities. At least one irregularity within the language input can be detected based upon the relative delta computation. The irregularity can include mumble, ambiguous input, and/or compound input. At least one programmatic action can be performed responsive to the detection of the irregularity.Type: ApplicationFiled: July 8, 2009Publication date: January 14, 2010Applicant: Nuance Communications, Inc.Inventors: Rajesh Balchandran, Linda M. Boyer