Patents by Inventor Jacob Daniel Andreas

Jacob Daniel Andreas 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: 20210050006
    Abstract: A computer-implemented method of responding to a conversational event. The method comprises enacting, by a conversational computing interface, an initial computer-executable plan based on a conversational event received by the conversational computing interface, wherein the initial computer-executable plan is configured to output an initial value based on the conversational event. The method further comprises selecting, by the conversational computing interface, an extended computer-executable plan based on determining that the initial value is insufficient for generating an extended description responsive to the conversational event. The method further comprises enacting, by the conversational computing interface, the extended computer-executable plan to output additional information beyond what the initial computer-executable plan is configured to output, the additional information sufficient for generating the extended description responsive to the conversational event.
    Type: Application
    Filed: October 18, 2019
    Publication date: February 18, 2021
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Jacob Daniel ANDREAS, Jayant Sivarama KRISHNAMURTHY, Alan Xinyu GUO, Andrei VOROBEV, John Philip BUFE, III, Jesse Daniel Eskes RUSAK, Yuchen ZHANG
  • Publication number: 20210026735
    Abstract: A method, comprising recognizing a user utterance for processing. The method further comprises using a previously-trained code-generation machine to generate, from the user utterance, a data-flow program configured to produce a return value upon successful execution. The method further comprises beginning execution of the data-flow program. Responsive to reaching an error condition resulting from execution of the data-flow program, the method further comprises, prior to the data-flow program producing the return value, suspending execution of the data flow program. The method further comprises using the previously-trained code-generation machine to generate an error-handling data-flow program, wherein the error-handling data-flow program is configured to produce the return value; beginning execution of the error-handling data-flow program to produce the return value; and outputting the return value.
    Type: Application
    Filed: July 23, 2019
    Publication date: January 28, 2021
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: David Leo Wright HALL, David Ernesto Heekin BURKETT, Jesse Daniel Eskes RUSAK, Alexander J. KOLMYKOV-ZOTOV, Jason Andrew WOLFE, Jacob Daniel ANDREAS, Adam David PAULS, John Philip BUFE, III, Jayant Sivarama KRISHNAMURTHY, Daniel Louis KLEIN
  • Publication number: 20210027771
    Abstract: A method comprising recognizing a user utterance including an ambiguity. The method further comprises using a previously-trained code-generation machine to produce, from the user utterance, a data-flow program including a search-history function. The search-history function is configured to select a highest-confidence disambiguating concept from one or more candidate concepts stored in a context-specific dialogue history.
    Type: Application
    Filed: July 23, 2019
    Publication date: January 28, 2021
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: David Leo Wright HALL, David Ernesto Heekin BURKETT, Jesse Daniel Eskes RUSAK, Jayant Sivarama KRISHNAMURTHY, Jason Andrew WOLFE, Adam David PAULS, Alan Xinyu GUO, Jacob Daniel ANDREAS, Daniel Louis KLEIN
  • Patent number: 10713288
    Abstract: A system that generates natural language content. The system generates and maintains a dialogue state representation having a process view, query view, and data view. The three-view dialogue state representation is continuously updated during discourse between an agent and a user, and rules can be automatically generated based on the discourse. Upon a content generation event, an object description can be generated based on the dialogue state representation. A string is then determined from the object description, using a hybrid approach of the automatically generated rules and other rules learned from annotation and other user input. The string is translated to text or speech and output by the agent. The present system also incorporates learning techniques, for example when ranking output and processing annotation templates.
    Type: Grant
    Filed: February 8, 2018
    Date of Patent: July 14, 2020
    Assignee: Semantic Machines, Inc.
    Inventors: Jacob Daniel Andreas, David Leo Wright Hall, Daniel Klein, Adam David Pauls
  • Publication number: 20190295545
    Abstract: A method for generating a dialogue event in a natural language processing system comprises loading, into a computer memory, a computer-readable seed command describing an ordered sequence of two or more top-level dialogue events. A dialogue event includes a client utterance or a computerized assistant response. The seed command includes one or more sub-commands, each sub-command corresponding to a portion of the ordered sequence of two or more top-level dialogue events, and the focal sub-command of the one or more sub-commands being parametrized by a seed semantic parameter. The method further comprises re-parametrizing the focal sub-command by outputting a plurality of different re-parametrized focal sub-commands wherein, in each re-parametrized focal sub-command, the seed semantic parameter is replaced by one of a plurality of different synthetic semantic parameters.
    Type: Application
    Filed: December 21, 2018
    Publication date: September 26, 2019
    Applicant: Semantic Machines, Inc.
    Inventors: Jacob Daniel ANDREAS, Daniel Louis KLEIN, David Leo Wright HALL, Laurence Steven GILLICK, Pengyu CHEN
  • Patent number: 10319381
    Abstract: An interaction assistant conducts multiple turn interaction dialogs with a user in which context is maintained between turns, and the system manages the dialog to achieve an inferred goal for the user. The system includes a linguistic interface to a user and a parser for processing linguistic events from the user. A dialog manager of the system is configured to receive alternative outputs from the parser, and selecting an action and causing the action to be performed based on the received alternative outputs. The system further includes a dialog state for an interaction with the user, and the alternative outputs represent alternative transitions from a current dialog state to a next dialog state. The system further includes a storage for a plurality of templates, and wherein each dialog state is defined in terms of an interrelationship of one or more instances of the templates.
    Type: Grant
    Filed: February 14, 2018
    Date of Patent: June 11, 2019
    Assignee: Semantic Machines, Inc.
    Inventors: Jacob Daniel Andreas, Daniel Lawrence Roth, Jesse Daniel Eskes Rusak, Andrew Robert Volpe, Steven Andrew Wegmann, Taylor Darwin Berg-Kirkpatrick, Pengyu Chen, Jordan Rian Cohen, Laurence Steven Gillick, David Leo Wright Hall, Daniel Klein, Michael Newman, Adam David Pauls
  • Patent number: 10276160
    Abstract: An interaction assistant conducts multiple turn interaction dialogs with a user in which context is maintained between turns, and the system manages the dialog to achieve an inferred goal for the user. The system includes a linguistic interface to a user and a parser for processing linguistic events from the user. A dialog manager of the system is configured to receive alternative outputs from the parser, and selecting an action and causing the action to be performed based on the received alternative outputs. The system further includes a dialog state for an interaction with the user, and the alternative outputs represent alternative transitions from a current dialog state to a next dialog state. The system further includes a storage for a plurality of templates, and wherein each dialog state is defined in terms of an interrelationship of one or more instances of the templates.
    Type: Grant
    Filed: November 10, 2016
    Date of Patent: April 30, 2019
    Assignee: Semantic Machines, Inc.
    Inventors: Jacob Daniel Andreas, Taylor Darwin Berg-Kirkpatrick, Pengyu Chen, Jordan Rian Cohen, Laurence Steven Gillick, David Leo Wright Hall, Daniel Klein, Michael Newman, Adam David Pauls, Daniel Lawrence Roth, Jesse Daniel Eskes Rusak, Andrew Robert Volpe, Steven Andrew Wegmann
  • Publication number: 20180246954
    Abstract: A system that generates natural language content. The system generates and maintains a dialogue state representation having a process view, query view, and data view. The three-view dialogue state representation is continuously updated during discourse between an agent and a user, and rules can be automatically generated based on the discourse. Upon a content generation event, an object description can be generated based on the dialogue state representation. A string is then determined from the object description, using a hybrid approach of the automatically generated rules and other rules learned from annotation and other user input. The string is translated to text or speech and output by the agent. The present system also incorporates learning techniques, for example when ranking output and processing annotation templates.
    Type: Application
    Filed: February 8, 2018
    Publication date: August 30, 2018
    Applicant: Semantic Machines, Inc.
    Inventors: Jacob Daniel Andreas, David Leo Wright Hall, Daniel Klein, Adam Pauls
  • Publication number: 20180061408
    Abstract: An automated assistant automatically recognizes speech, decode paraphrases in the recognized speech, performs an action or task based on the decoder output, and provides a response to the user. The response may be text or audio, and may be translated to include paraphrasing. The automatically recognized speech may be processed to determine partitions in the speech, which may be in turn processed to identify paraphrases in the partitions. A decoder may process an input utterance text to identify paraphrases content to include in a segment or sentence. The decoder may paraphrase the input utterance to make the utterance, updated with one or more paraphrases, more easily parsed by a parser. A translator may process a generated response to make the response sound more natural. The translator may replace content of the generated response with paraphrase content based on the state of the conversation with the user, including salience data.
    Type: Application
    Filed: August 4, 2017
    Publication date: March 1, 2018
    Applicant: Semantic Machines, Inc.
    Inventors: Jacob Daniel Andreas, David Ernesto Heekin Burkett, Pengyu Chen, Jordan Rian Cohen, Gregory Christopher Durrett, Laurence Steven Gillick, David Leo Wright Hall, Daniel Klein, Adam David Pauls, Daniel Lawrence Roth, Jesse Daniele Eskes Rusak, Yan Virin, Charles Clayton Wooters