Patents by Inventor Sonal Gupta
Sonal Gupta 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: 20240155071Abstract: A method and system for text-to-video generation. The method includes receiving a text input, generating a representation frame based on the text input using a model trained on text-image pairs, generating a set of frames based on the representation frame and a first frame rate, interpolating the set of frames to a higher frame rate, generating a first video based on the interpolated set of frames, increasing a resolution of the first video based on a first and second super-resolution model, and generating an output video based on a result of the super-resolution models.Type: ApplicationFiled: September 29, 2023Publication date: May 9, 2024Inventors: Sonal Gupta, Adam Polyak, Thomas Falstad Hayes, Xi Yin, Jie An, Chao Yang, Oron Ashual, Oran Gafni, Devi Niru Parikh, Yaniv Nechemia Taigman, Uriel Singer, Songyang Zhang, Qiyuan Hu
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Patent number: 11688022Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.Type: GrantFiled: August 20, 2020Date of Patent: June 27, 2023Assignee: Meta Platforms, Inc.Inventors: Armen Aghajanyan, Sonal Gupta, Brian Moran, Theodore Frank Levin, Crystal Annette Naomi Su Hua Nakatsu, Daniel Difranco, Jonathan David Christensen, Kirk LaBuda, Anuj Kumar
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Patent number: 11651449Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.Type: GrantFiled: August 20, 2020Date of Patent: May 16, 2023Assignee: Meta Platforms, Inc.Inventors: Armen Aghajanyan, Sonal Gupta, Brian Moran, Theodore Frank Levin, Crystal Annette Naomi Su Hua Nakatsu, Daniel Difranco, Jonathan David Christensen, Kirk LaBuda, Anuj Kumar
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Patent number: 11615484Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.Type: GrantFiled: August 20, 2020Date of Patent: March 28, 2023Assignee: Meta Platforms, Inc.Inventors: Armen Aghajanyan, Sonal Gupta, Brian Moran, Theodore Frank Levin, Crystal Annette Naomi Su Hua Nakatsu, Daniel Difranco, Jonathan David Christensen, Kirk LaBuda, Anuj Kumar
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Patent number: 11586823Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.Type: GrantFiled: August 20, 2020Date of Patent: February 21, 2023Assignee: Meta Platforms, Inc.Inventors: Armen Aghajanyan, Sonal Gupta, Brian Moran, Theodore Frank Levin, Crystal Annette Naomi Su Hua Nakatsu, Daniel Difranco, Jonathan David Christensen, Kirk LaBuda, Anuj Kumar
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Publication number: 20220415320Abstract: In one embodiment, a system includes an automatic speech recognition (ASR) module, a natural-language understanding (NLU) module, a dialog manager, one or more agents, an arbitrator, a delivery system, one or more processors, and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to receive a user input, process the user input using the ASR module, the NLU module, the dialog manager, one or more of the agents, the arbitrator, and the delivery system, and provide a response to the user input.Type: ApplicationFiled: May 16, 2022Publication date: December 29, 2022Inventors: Pujie Zheng, Lin Sun, Ram Kumar Hariharan, Haidong Wang, Joshua Saylor McMullen, Mengxi Li, Long You Cai, Keith Diedrick, Crystal Annette Nakatsu Sung, Xi Chen, Stanislav Peshterliev, Debojeet Chatterjee, Sonal Gupta, Vikas Seshagiri Rao Bhardwaj, Yashar Mehdad, Anuj Kumar, Ashish Garg, Justin Denney, Hakan Inan, Iaroslav Markov, Surya Teja Appini, Bing Liu, Shusen Liu, Zhiqi Wang, Alexander Kolmykov-Zotov
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Publication number: 20210117624Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.Type: ApplicationFiled: August 20, 2020Publication date: April 22, 2021Inventors: Armen Aghajanyan, Sonal Gupta, Brian Moran, Theodore Frank Levin, Crystal Annette Naomi Su Hua Nakatsu, Daniel Difranco, Jonathan David Christensen, Kirk LaBuda, Anuj Kumar
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Publication number: 20100208984Abstract: A source keyword may be received multiple times and each time, in response, a machine-learning algorithm may be used to identify and rank respective matching-keywords that have been determined to match the source keyword. A portion or unit of content may be generated based on one of the ranked matching-keywords. The content is transmitted via a network to a client device and a user's impression of the content is recorded. The machine-learning algorithm may continue to rank matching-keywords for arbitrary source keywords while the recorded impressions and corresponding matched-keywords, respectively, are used to train the machine-learning algorithm. The training alters how the machine-learning algorithm ranks matching-keywords determined to match the source keyword.Type: ApplicationFiled: February 13, 2009Publication date: August 19, 2010Applicant: MICROSOFT CORPORATIONInventors: Mikhail Bilenko, Matthew Richardson, Sonal Gupta