Patents by Inventor William Brennan Dolan
William Brennan Dolan 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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Publication number: 20230385320Abstract: Systems and methods are directed to generating content that is contextually relevant in a writing style of a user. In example embodiments, a plurality of logical inputs regarding a topic is received in bullet point format. A content generator generates draft content using machine learning (ML) models. The generating comprises identifying a writing style of the user by applying the plurality of logical inputs to a first ML model, determining a context and direction for the draft content using a second ML model, and based on the plurality of logical inputs, the identified writing style, and the context and direction, generating at least one paragraph of draft content in the writing style of the user that follows an outline associated with the bullet point format and comprises a same context and direction as the plurality of logical inputs. The draft content is then presented at a client device.Type: ApplicationFiled: June 9, 2022Publication date: November 30, 2023Inventors: Weixin CAI, Si-Qing Chen, Michel Galley, William Brennan Dolan, Christopher J. Brockett, Zhang Li, Warren A. Aldred, Xinyu He, Jesse Alexander Freitas, Kaushik Ramaiah Narayanan
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Publication number: 20230325603Abstract: A controllable grounded response generation framework includes a machine learning model, a grounding interface, and a control interface. The machine learning model is trained to output computer-generated text based on input text. The grounding interface is useable by the machine learning model to access a grounding source including information related to the input text. The control interface is useable by the machine learning model to recognize a control signal. The machine learning model is configured to include information from the grounding source in the computer-generated text and focus the computer-generated text based on the control signal.Type: ApplicationFiled: June 13, 2023Publication date: October 12, 2023Applicant: Microsoft Technology Licensing, LLCInventors: Michel GALLEY, Christopher Brian QUIRK, William Brennan DOLAN, Zeqiu WU
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Patent number: 11741306Abstract: A controllable grounded response generation framework includes a machine learning model, a grounding interface, and a control interface. The machine learning model is trained to output computer-generated text based on input text. The grounding interface is useable by the machine learning model to access a grounding source including information related to the input text. The control interface is useable by the machine learning model to recognize a control signal. The machine learning model is configured to include information from the grounding source in the computer-generated text and focus the computer-generated text based on the control signal.Type: GrantFiled: March 12, 2020Date of Patent: August 29, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Michel Galley, Christopher Brian Quirk, William Brennan Dolan, Zeqiu Wu
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Patent number: 11429779Abstract: A method and system for providing replacement text segments for a given text segment may include receiving a request to provide the replacement text segment for the text segment in the document, examining a content characteristic of the document, and examining at least one of user-specific information, organization-specific information, or non-linguistic features of the document, before identifying at least one replacement text segment for the text segment, via a machine translation system, based on the content characteristic of the document and at least one of the user-specific information, the organization-specific information, or the non-linguistic features of the document. The method and system may include providing the identified replacement text segment for display to a user, receiving an input indicating a user's selection of the identified replacement text segment, and upon receiving the input, replacing the text segment in the document with the identified replacement text segment.Type: GrantFiled: July 1, 2019Date of Patent: August 30, 2022Assignee: Microsoft Technology Licensing, LLCInventors: Zhang Li, Domenic Joseph Cipollone, Maria Isabel Carpenter, Juhi Amitkumar Naik, Susan Michele Hendrich, Michael Wilson Daniels, William Brennan Dolan, Christopher Brian Quirk, Christopher John Brockett, Alice Yingming Lai
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Patent number: 11126794Abstract: A method for providing targeted rewrites can include receiving a selection of text in a file; generating a set of target rewrites of the selection of text, the set of target rewrites comprising: at least one phrase or sentence having semantic similarity to a phrase or sentence of the selection of text; and a style that corresponds to a particular target style, wherein a target style is a representative style for a genre, profession, or environment; and providing for selection one or more of the target rewrites of the set of target rewrites.Type: GrantFiled: April 11, 2019Date of Patent: September 21, 2021Assignee: Microsoft Technology Licensing, LLCInventors: Zhang Li, Christopher John Brockett, William Brennan Dolan, Christopher Brian Quirk, Alice Yingming Lai, Susan Michele Hendrich, Olivier Gauthier, Kaushik Ramaiah Narayanan, Maria Isabel Carpenter, Juhi Amitkumar Naik, Michael Wilson Daniels
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Publication number: 20210192140Abstract: A controllable grounded response generation framework includes a machine learning model, a grounding interface, and a control interface. The machine learning model is trained to output computer-generated text based on input text. The grounding interface is useable by the machine learning model to access a grounding source including information related to the input text. The control interface is useable by the machine learning model to recognize a control signal. The machine learning model is configured to include information from the grounding source in the computer-generated text and focus the computer-generated text based on the control signal.Type: ApplicationFiled: March 12, 2020Publication date: June 24, 2021Applicant: Microsoft Technology Licensing, LLCInventors: Michel GALLEY, Christopher Brian QUIRK, William Brennan DOLAN, Zeqiu WU
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Publication number: 20210004432Abstract: A method and system for providing replacement text segments for a given text segment may include receiving a request to provide the replacement text segment for the text segment in the document, examining a content characteristic of the document, and examining at least one of user-specific information, organization-specific information, or non-linguistic features of the document, before identifying at least one replacement text segment for the text segment, via a machine translation system, based on the content characteristic of the document and at least one of the user-specific information, the organization-specific information, or the non-linguistic features of the document. The method and system may include providing the identified replacement text segment for display to a user, receiving an input indicating a user's selection of the identified replacement text segment, and upon receiving the input, replacing the text segment in the document with the identified replacement text segment.Type: ApplicationFiled: July 1, 2019Publication date: January 7, 2021Applicant: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Zhang LI, Domenic Joseph CIPOLLONE, Maria Isabel CARPENTER, Juhi Amitkumar NAIK, Susan Michele HENDRICH, Michael Wilson DANIELS, William Brennan DOLAN, Christopher Brian QUIRK, Christopher John BROCKETT, Alice Yingming LAI
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Publication number: 20200327189Abstract: A method for providing targeted rewrites can include receiving a selection of text in a file; generating a set of target rewrites of the selection of text, the set of target rewrites comprising: at least one phrase or sentence having semantic similarity to a phrase or sentence of the selection of text; and a style that corresponds to a particular target style, wherein a target style is a representative style for a genre, profession, or environment; and providing for selection one or more of the target rewrites of the set of target rewrites.Type: ApplicationFiled: April 11, 2019Publication date: October 15, 2020Inventors: Zhang LI, Christopher John BROCKETT, William Brennan DOLAN, Christopher Brian QUIRK, Alice Yingming LAI, Susan Michele HENDRICH, Olivier GAUTHIER, Kaushik Ramaiah NARAYANAN, Maria Isabel CARPENTER, Juhi Amitkumar NAIK, Michael Wilson DANIELS
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Patent number: 10536402Abstract: Examples are generally directed towards context-sensitive generation of conversational responses. Context-message-response n-tuples are extracted from at least one source of conversational data to generate a set of training context-message-response n-tuples. A response generation engine is trained on the set of training context-message-response n-tuples. The trained response generation engine automatically generates a context-sensitive response based on a user generated input message and conversational context data. A digital assistant utilizes the trained response generation engine to generate context-sensitive, natural language responses that are pertinent to user queries.Type: GrantFiled: August 24, 2018Date of Patent: January 14, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Michel Galley, Alessandro Sordoni, Christopher John Brockett, Jianfeng Gao, William Brennan Dolan, Yangfeng Ji, Michael Auli, Margaret Ann Mitchell, Jian-Yun Nie
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Publication number: 20190354594Abstract: Conversations can be generated automatically based on any given persona. The conversations can be produced by a language generation model that automatically generates persona-based language in response to a message, wherein a persona identifies a type of person with role specific characteristics. After a language generation model is acquired, for example by identifying a predefined model or generating a new model, the language generation model can be provisioned for use by a conversational agent, such as a chatbot, to enhance the functionality of the conversational agent.Type: ApplicationFiled: May 20, 2018Publication date: November 21, 2019Inventors: Jonathan Burgess Foster, Tulasi Menon, William Brennan Dolan, Radhakrishnan Srikanth, Sai Tulasi Neppali, Michel Galley, Christopher John Brockett, Parag Agrawal, Rohan Kulkarni, Ronald Kevin Owens, Deborah Briana Harrison
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Publication number: 20180367475Abstract: Examples are generally directed towards context-sensitive generation of conversational responses. Context-message-response n-tuples are extracted from at least one source of conversational data to generate a set of training context-message-response n-tuples. A response generation engine is trained on the set of training context-message-response n-tuples. The trained response generation engine automatically generates a context-sensitive response based on a user generated input message and conversational context data. A digital assistant utilizes the trained response generation engine to generate context-sensitive, natural language responses that are pertinent to user queries.Type: ApplicationFiled: August 24, 2018Publication date: December 20, 2018Inventors: Michel GALLEY, Alessandro SORDONI, Christopher John BROCKETT, Jianfeng GAO, William Brennan DOLAN, Yangfeng JI, Michael AULI, Margaret Ann MITCHELL, Jian-Yun NIE
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Patent number: 10091140Abstract: Examples are generally directed towards context-sensitive generation of conversational responses. Context-message-response n-tuples are extracted from at least one source of conversational data to generate a set of training context-message-response n-tuples. A response generation engine is trained on the set of training context-message-response n-tuples. The trained response generation engine automatically generates a context-sensitive response based on a user generated input message and conversational context data. A digital assistant utilizes the trained response generation engine to generate context-sensitive, natural language responses that are pertinent to user queries.Type: GrantFiled: May 31, 2015Date of Patent: October 2, 2018Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Michel Galley, Alessandro Sordoni, Christopher John Brockett, Jianfeng Gao, William Brennan Dolan, Yangfeng Ji, Michael Auli, Margaret Ann Mitchell, Jian-Yun Nie
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Patent number: 9967211Abstract: Examples are generally directed towards automatic assessment of machine generated conversational responses. Context-message-response n-tuples are extracted from at least one source of conversational data to generate a set of multi-reference responses. A response in the set of multi-reference responses includes it context-message data pair and rating. The rating indicates a quality of the response relative to the context-message data pair. A response assessment engine generates a metric score for a machine-generated response based on an assessment metric and the set of multi-reference responses. The metric score indicates a quality of the machine-generated conversational response relative to a user-generated message and a context of the user-generated message. A response generation system of a computing device, such as a digital assistant, is optimized and adjusted based on the metric score to improve the accuracy, quality, and relevance of responses output to the user.Type: GrantFiled: May 31, 2015Date of Patent: May 8, 2018Assignee: Microsoft Technology Licensing, LLCInventors: Michel Galley, Alessandro Sordoni, Christopher John Brockett, Jianfeng Gao, William Brennan Dolan, Yangfeng Ji, Michael Auli, Margaret Ann Mitchell, Christopher Brian Quirk
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Patent number: 9754585Abstract: Different advantageous embodiments provide a crowdsourcing method for modeling user intent in conversational interfaces. One or more stimuli are presented to a plurality of describers. One or more sets of describer data are captured from the plurality of describers using a data collection mechanism. The one or more sets of describer data are processed to generate one or more models. Each of the one or more models is associated with a specific stimulus from the one or more stimuli.Type: GrantFiled: April 3, 2012Date of Patent: September 5, 2017Assignee: Microsoft Technology Licensing, LLCInventors: Christopher John Brockett, Piali Choudhury, William Brennan Dolan, Yun-Cheng Ju, Patrick Pantel, Noelle Mallory Sophy, Svitlana Volkova
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Publication number: 20160352657Abstract: Examples are generally directed towards automatic assessment of machine generated conversational responses. Context-message-response n-tuples are extracted from at least one source of conversational data to generate a set of multi-reference responses. A response in the set of multi-reference responses includes it context-message data pair and rating. The rating indicates a quality of the response relative to the context-message data pair. A response assessment engine generates a metric score for a machine-generated response based on an assessment metric and the set of multi-reference responses. The metric score indicates a quality of the machine-generated conversational response relative to a user-generated message and a context of the user-generated message. A response generation system of a computing device, such as a digital assistant, is optimized and adjusted based on the metric score to improve the accuracy, quality, and relevance of responses output to the user.Type: ApplicationFiled: May 31, 2015Publication date: December 1, 2016Inventors: Michel GALLEY, Alessandro SORDONI, Christopher John BROCKETT, Jianfeng GAO, III, William Brennan DOLAN, Yangfeng JI, Michael AULI, Margaret Ann MITCHELL, Christopher Brian QUIRK
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Publication number: 20160352656Abstract: Examples are generally directed towards context-sensitive generation of conversational responses. Context-message-response n-tuples are extracted from at least one source of conversational data to generate a set of training context-message-response n-tuples. A response generation engine is trained on the set of training context-message-response n-tuples. The trained response generation engine automatically generates a context-sensitive response based on a user generated input message and conversational context data. A digital assistant utilizes the trained response generation engine to generate context-sensitive, natural language responses that are pertinent to user queries.Type: ApplicationFiled: May 31, 2015Publication date: December 1, 2016Inventors: Michel GALLEY, Alessandro SORDONI, Christopher John BROCKETT, Jianfeng GAO, III, William Brennan DOLAN, Yangfeng JI, Michael AULI, Margaret Ann MITCHELL, Jian-Yun NIE
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Patent number: 8972240Abstract: An “Interactive Word Lattice” provides a user interface for interacting with and selecting user-modifiable paths through a lattice-based representation of alternative suggested text segments in response to a user's text segment input, such as phrases, sentences, paragraphs, entire documents, etc. More specifically, the user input is provided to a trained paraphrase generation model that returns a plurality of alternative text segments having the same or similar meaning as the original user input. An interactive graphical lattice-based representation of the alternative text segments is then presented to the user. One or more words of each alternative text segment represents a “node” of the lattice, while each connection between nodes represents a lattice “edge. Both nodes and edges are user modifiable. Each possible path through the lattice corresponds to a different alternative text segment. Users select a path through the lattice to select an alternative text to the original input.Type: GrantFiled: August 18, 2011Date of Patent: March 3, 2015Assignee: Microsoft CorporationInventors: Christopher John Brockett, William Brennan Dolan
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Publication number: 20130262114Abstract: Different advantageous embodiments provide a crowdsourcing method for modeling user intent in conversational interfaces. One or more stimuli are presented to a plurality of describers. One or more sets of describer data are captured from the plurality of describers using a data collection mechanism. The one or more sets of describer data are processed to generate one or more models. Each of the one or more models is associated with a specific stimulus from the one or more stimuli.Type: ApplicationFiled: April 3, 2012Publication date: October 3, 2013Applicant: MICROSOFT CORPORATIONInventors: Christopher John Brockett, Piali Choudhury, William Brennan Dolan, Yun-Cheng Ju, Patrick Pantel, Noelle Mallory Sophy, Svitlana Volkova
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Publication number: 20120296635Abstract: An “Interactive Word Lattice” provides a user interface for interacting with and selecting user-modifiable paths through a lattice-based representation of alternative suggested text segments in response to a user's text segment input, such as phrases, sentences, paragraphs, entire documents, etc. More specifically, the user input is provided to a trained paraphrase generation model that returns a plurality of alternative text segments having the same or similar meaning as the original user input. An interactive graphical lattice-based representation of the alternative text segments is then presented to the user. One or more words of each alternative text segment represents a “node” of the lattice, while each connection between nodes represents a lattice “edge. Both nodes and edges are user modifiable. Each possible path through the lattice corresponds to a different alternative text segment. Users select a path through the lattice to select an alternative text to the original input.Type: ApplicationFiled: August 18, 2011Publication date: November 22, 2012Applicant: Microsoft CorporationInventors: Christopher John Brockett, William Brennan Dolan