Patents by Inventor Sarangarajan Parthasarathy

Sarangarajan Parthasarathy 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).

  • Publication number: 20170011025
    Abstract: Sentence simplification may be provided. A spoken phrase may be received and converted to a text phrase. An intent associated with the text phrase may be identified. The text phrase may then be reformatted according to the identified intent and a task may be performed according to the reformatted text phrase.
    Type: Application
    Filed: September 21, 2016
    Publication date: January 12, 2017
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Gokhan Tur, Dilek Hakkani-Tur, Larry Paul Heck, Sarangarajan Parthasarathy
  • Patent number: 9529794
    Abstract: The customization of language modeling components for speech recognition is provided. A list of language modeling components may be made available by a computing device. A hint may then be sent to a recognition service provider for combining the multiple language modeling components from the list. The hint may be based on a number of different domains. A customized combination of the language modeling components based on the hint may then be received from the recognition service provider.
    Type: Grant
    Filed: March 27, 2014
    Date of Patent: December 27, 2016
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Michael Levit, Hernan Guelman, Shuangyu Chang, Sarangarajan Parthasarathy, Benoit Dumoulin
  • Patent number: 9460081
    Abstract: Examples of the present disclosure describe generation of a multi-arc confusion network to improve, for example, an ability to return alternatives to output generated. A confusion network comprising token representations of lexicalized hypotheses and normalized hypotheses is generated. Each arc of the confusion network represents a token of a lexicalized hypothesis or a normalized hypothesis. The confusion network is transformed into a multi-arc confusion network, wherein the transforming comprising realigning at least one token of the confusion network to span multiple arcs of the confusion network. Other examples are also described.
    Type: Grant
    Filed: June 2, 2016
    Date of Patent: October 4, 2016
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Michael Levit, Umut Ozertem, Sarangarajan Parthasarathy, Padma Varadharajan, Karthik Raghunathan, Issac Alphonso
  • Patent number: 9460709
    Abstract: A system and method of updating automatic speech recognition parameters on a mobile device are disclosed. The method comprises storing user account-specific adaptation data associated with ASR on a computing device associated with a wireless network, generating new ASR adaptation parameters based on transmitted information from the mobile device when a communication channel between the computing device and the mobile device becomes available and transmitting the new ASR adaptation data to the mobile device when a communication channel between the computing device and the mobile device becomes available. The new ASR adaptation data on the mobile device more accurately recognizes user utterances.
    Type: Grant
    Filed: March 26, 2014
    Date of Patent: October 4, 2016
    Assignee: AT&T Intellectual Property II, L.P.
    Inventors: Sarangarajan Parthasarathy, Richard Cameron Rose
  • Patent number: 9454962
    Abstract: Sentence simplification may be provided. A spoken phrase may be received and converted to a text phrase. An intent associated with the text phrase may be identified. The text phrase may then be reformatted according to the identified intent and a task may be performed according to the reformatted text phrase.
    Type: Grant
    Filed: May 12, 2011
    Date of Patent: September 27, 2016
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Gokhan Tur, Dilek Hakkani-Tur, Larry Paul Heck, Sarangarajan Parthasarathy
  • Publication number: 20160275071
    Abstract: Examples of the present disclosure describe generation of a multi-arc confusion network to improve, for example, an ability to return alternatives to output generated. A confusion network comprising token representations of lexicalized hypotheses and normalized hypotheses is generated. Each arc of the confusion network represents a token of a lexicalized hypothesis or a normalized hypothesis. The confusion network is transformed into a multi-arc confusion network, wherein the transforming comprising realigning at least one token of the confusion network to span multiple arcs of the confusion network. Other examples are also described.
    Type: Application
    Filed: June 2, 2016
    Publication date: September 22, 2016
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Michael Levit, Umut Ozertem, Sarangarajan Parthasarathy, Padma Varadharajan, Karthik Raghunathan, Issac Alphonso
  • Publication number: 20160267905
    Abstract: Optimized language models are provided for in-domain applications through an iterative, joint-modeling approach that interpolates a language model (LM) from a number of component LMs according to interpolation weights optimized for a target domain. The component LMs may include class-based LMs, and the interpolation may be context-specific or context-independent. Through iterative processes, the component LMs may be interpolated and used to express training material as alternative representations or parses of tokens. Posterior probabilities may be determined for these parses and used for determining new (or updated) interpolation weights for the LM components, such that a combination or interpolation of component LMs is further optimized for the domain. The component LMs may be merged, according to the optimized weights, into a single, combined LM, for deployment in an application scenario.
    Type: Application
    Filed: March 11, 2015
    Publication date: September 15, 2016
    Inventors: Michael Levit, Sarangarajan Parthasarathy, Andreas Stolcke, Shuangyu Chang
  • Publication number: 20160267128
    Abstract: Methods and systems are provided for providing alternative query suggestions. For example, a spoken natural language expression may be received and converted to a textual query by a speech recognition component. The spoken natural language expression may include one or more words, terms, and/or phrases. A phonetically confusable segment of the textual query may be identified by a classifier component. The classifier component may determine at least one alternative query based on identifying at least the phonetically confusable segment of the textual query. The classifier may further determine whether to suggest the at least one alternative query based on whether the at least one alternative query is sensical and/or useful. When it is determined to suggest the at least one alternative query, the at least one alternative query may be provided to and displayed on a user interface display.
    Type: Application
    Filed: March 13, 2015
    Publication date: September 15, 2016
    Applicant: Microsoft Technology Licensing , LLC
    Inventors: Benoit Dumoulin, Ali Ahmadi, Sarangarajan Parthasarathy, Nick Craswell, Umut Ozertem, Milad Shokouhi, Karthik Raghunathan, Rosie Jones
  • Publication number: 20160217125
    Abstract: Examples of the present disclosure describe generation of a multi-arc confusion network to improve, for example, an ability to return alternatives to output generated. A confusion network comprising token representations of lexicalized hypotheses and normalized hypotheses is generated. Each arc of the confusion network represents a token of a lexicalized hypothesis or a normalized hypothesis. The confusion network is transformed into a multi-arc confusion network, wherein the transforming comprising realigning at least one token of the confusion network to span multiple arcs of the confusion network. Other examples are also described.
    Type: Application
    Filed: January 27, 2015
    Publication date: July 28, 2016
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Michael Levit, Umut Ozertem, Sarangarajan Parthasarathy, Padma Varadharajan, Karthik Raghunathan, Issac Alphonso
  • Publication number: 20160196822
    Abstract: A system and method of updating automatic speech recognition parameters on a mobile device are disclosed. The method comprises storing user account-specific adaptation data associated with ASR on a computing device associated with a wireless network, generating new ASR adaptation parameters based on transmitted information from the mobile device when a communication channel between the computing device and the mobile device becomes available and transmitting the new ASR adaptation data to the mobile device when a communication channel between the computing device and the mobile device becomes available. The new ASR adaptation data on the mobile device more accurately recognizes user utterances.
    Type: Application
    Filed: March 16, 2016
    Publication date: July 7, 2016
    Inventors: Sarangarajan PARTHASARATHY, Richard Cameron ROSE
  • Patent number: 9384188
    Abstract: Examples of the present disclosure describe generation of a multi-arc confusion network to improve, for example, an ability to return alternatives to output generated. A confusion network comprising token representations of lexicalized hypotheses and normalized hypotheses is generated. Each arc of the confusion network represents a token of a lexicalized hypothesis or a normalized hypothesis. The confusion network is transformed into a multi-arc confusion network, wherein the transforming comprising realigning at least one token of the confusion network to span multiple arcs of the confusion network. Other examples are also described.
    Type: Grant
    Filed: January 27, 2015
    Date of Patent: July 5, 2016
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Michael Levit, Umut Ozertem, Sarangarajan Parthasarathy, Padma Varadharajan, Karthik Raghunathan, Issac Alphonso
  • Publication number: 20160078868
    Abstract: Techniques are described herein that are capable of suggesting intent frame(s) for user request(s). For instance, the intent frame(s) may be suggested to elicit a request from a user. An intent frame is a natural language phrase (e.g., a sentence) that includes at least one carrier phrase and at least one slot. A slot in an intent frame is a placeholder that is identified as being replaceable by one or more words that identify an entity and/or an action to indicate an intent of the user. A carrier phrase in an intent frame includes one or more words that suggest a type of entity and/or action that is to be identified by the one or more words that may replace the corresponding slot. In accordance with these techniques, the intent frame(s) are suggested in response to determining that natural language functionality of a processing system is activated.
    Type: Application
    Filed: November 29, 2015
    Publication date: March 17, 2016
    Inventors: Shane J. Landry, Anne K. Sullivan, Lisa J. Stifelman, Adam D. Elman, Larry Paul Heck, Sarangarajan Parthasarathy
  • Publication number: 20160042732
    Abstract: A method, apparatus and machine-readable medium are provided. A phonotactic grammar is utilized to perform speech recognition on received speech and to generate a phoneme lattice. A document shortlist is generated based on using the phoneme lattice to query an index. A grammar is generated from the document shortlist. Data for each of at least one input field is identified based on the received speech and the generated grammar.
    Type: Application
    Filed: October 19, 2015
    Publication date: February 11, 2016
    Inventors: Cyril Georges Luc ALLAUZEN, Sarangarajan PARTHASARATHY
  • Patent number: 9201859
    Abstract: Techniques are described herein that are capable of suggesting intent frame(s) for user request(s). For instance, the intent frame(s) may be suggested to elicit a request from a user. An intent frame is a natural language phrase (e.g., a sentence) that includes at least one carrier phrase and at least one slot. A slot in an intent frame is a placeholder that is identified as being replaceable by one or more words that identify an entity and/or an action to indicate an intent of the user. A carrier phrase in an intent frame includes one or more words that suggest a type of entity and/or action that is to be identified by the one or more words that may replace the corresponding slot. In accordance with these techniques, the intent frame(s) are suggested in response to determining that natural language functionality of a processing system is activated.
    Type: Grant
    Filed: December 15, 2011
    Date of Patent: December 1, 2015
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Shane J. Landry, Anne K. Sullivan, Lisa J. Stifelman, Adam D. Elman, Larry Paul Heck, Sarangarajan Parthasarathy
  • Publication number: 20150325235
    Abstract: Systems and methods are provided for optimizing language models for in-domain applications through an iterative, joint-modeling approach that expresses training material as alternative representations of higher-level tokens, such as named entities and carrier phrases. From a first language model, an in-domain training corpus may be represented as a set of alternative parses of tokens. Statistical information determined from these parsed representations may be used to produce a second (or updated) language model, which is further optimized for the domain. The second language model may be used to determine another alternative parsed representation of the corpus for a next iteration, and the statistical information determined from this representation may be used to produce a third (or further updated) language model. Through each iteration, a language model may be determined that is further optimized for the domain.
    Type: Application
    Filed: May 7, 2014
    Publication date: November 12, 2015
    Applicant: Microsoft Corporation
    Inventors: Michael Levit, Sarangarajan Parthasarathy, Andreas Stolcke
  • Patent number: 9165554
    Abstract: A method, apparatus and machine-readable medium are provided. A phonotactic grammar is utilized to perform speech recognition on received speech and to generate a phoneme lattice. A document shortlist is generated based on using the phoneme lattice to query an index. A grammar is generated from the document shortlist. Data for each of at least one input field is identified based on the received speech and the generated grammar.
    Type: Grant
    Filed: December 4, 2014
    Date of Patent: October 20, 2015
    Assignee: AT&T Intellectual Property II, L.P.
    Inventors: Cyril Georges Luc Allauzen, Sarangarajan Parthasarathy
  • Publication number: 20150278191
    Abstract: The customization of language modeling components for speech recognition is provided. A list of language modeling components may be made available by a computing device. A hint may then be sent to a recognition service provider for combining the multiple language modeling components from the list. The hint may be based on a number of different domains. A customized combination of the language modeling components based on the hint may then be received from the recognition service provider.
    Type: Application
    Filed: March 27, 2014
    Publication date: October 1, 2015
    Applicant: Microsoft Corporation
    Inventors: Michael Levit, Hernan Guelman, Shuangyu Chang, Sarangarajan Parthasarathy, Benoit Dumoulin
  • Publication number: 20150269136
    Abstract: Various components provide options to re-format an input based on one or more contexts. The input is received that has been submitted to an application (e.g., messaging application, mobile application, word-processing application, web browser, search tool, etc.), and one or more outputs are identified that are possibilities to be provided as options for re-formatting. A respective score of each output is determined by applying a statistical model to a respective combination of the input and each output, the respective score comprising a plurality of context scores that quantify a plurality of contexts of the respective combination. Exemplary contexts include historical-user contexts, domain contexts, and general contexts. One or more suggested outputs are selected from among the one or more outputs based on the respective scores and are provided as options to re-format the input.
    Type: Application
    Filed: March 20, 2014
    Publication date: September 24, 2015
    Applicant: MICROSOFT CORPORATION
    Inventors: ISSAC ALPHONSO, NICK KIBRE, MICHAEL LEVIT, SARANGARAJAN PARTHASARATHY
  • Publication number: 20150243278
    Abstract: A new pronunciation learning system for dynamically learning new pronunciations assisted by user correction logs. The user correction logs provide a record of speech recognition events and subsequent user behavior that implicitly confirms or rejects the recognition result and/or shows the user's intended words by via subsequent input. The system analyzes the correction logs and distills them down to a set of words which lack acceptable pronunciations. Hypothetical pronunciations, constrained by spelling and other linguistic knowledge, are generated for each of the words. Offline recognition determines the hypothetical pronunciations with a good acoustical match to the audio data likely to contain the words. The matching pronunciations are aggregated and adjudicated to select new pronunciations for the words to improve general or personalized recognition models.
    Type: Application
    Filed: February 21, 2014
    Publication date: August 27, 2015
    Applicant: MICROSOFT CORPORATION
    Inventors: Nicholas Kibre, Umut Ozertem, Sarangarajan Parthasarathy, Ziad Al Bawab
  • Patent number: 9058810
    Abstract: Speech recognition models are dynamically re-configurable based on user information, application information, background information such as background noise and transducer information such as transducer response characteristics to provide users with alternate input modes to keyboard text entry. Word recognition lattices are generated for each data field of an application and dynamically concatenated into a single word recognition lattice. A language model is applied to the concatenated word recognition lattice to determine the relationships between the word recognition lattices and repeated until the generated word recognition lattices are acceptable or differ from a predetermined value only by a threshold amount. These techniques of dynamic re-configurable speech recognition provide for deployment of speech recognition on small devices such as mobile phones and personal digital assistants as well environments such as office, home or vehicle while maintaining the accuracy of the speech recognition.
    Type: Grant
    Filed: March 26, 2012
    Date of Patent: June 16, 2015
    Assignee: AT&T Intellectual Property II, L.P.
    Inventors: Bojana Gajic, Shrikanth Sambasivan Narayanan, Sarangarajan Parthasarathy, Richard Cameron Rose, Aaron Edward Rosenberg