Patents by Inventor James Kuczmarski
James Kuczmarski 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: 11942082Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.Type: GrantFiled: May 26, 2022Date of Patent: March 26, 2024Assignee: GOOGLE LLCInventors: James Kuczmarski, Vibhor Jain, Amarnag Subramanya, Nimesh Ranjan, Melvin Jose Johnson Premkumar, Vladimir Vuskovic, Luna Dai, Daisuke Ikeda, Nihal Sandeep Balani, Jinna Lei, Mengmeng Niu, Hongjie Chai, Wangqing Yuan
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Patent number: 11915692Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.Type: GrantFiled: March 24, 2021Date of Patent: February 27, 2024Assignee: GOOGLE LLCInventors: James Kuczmarski, Vibhor Jain, Amarnag Subramanya, Nimesh Ranjan, Melvin Jose Johnson Premkumar, Vladimir Vuskovic, Luna Dai, Daisuke Ikeda, Nihal Sandeep Balani, Jinna Lei, Mengmeng Niu
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Patent number: 11875788Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.Type: GrantFiled: March 24, 2021Date of Patent: January 16, 2024Assignee: GOOGLE LLCInventors: James Kuczmarski, Vibhor Jain, Amarnag Subramanya, Nimesh Ranjan, Melvin Jose Johnson Premkumar, Vladimir Vuskovic, Luna Dai, Daisuke Ikeda, Nihal Sandeep Balani, Jinna Lei, Mengmeng Niu
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Publication number: 20220284198Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.Type: ApplicationFiled: May 26, 2022Publication date: September 8, 2022Inventors: James Kuczmarski, Vibhor Jain, Amarnag Subramanya, Nimesh Ranjan, Melvin Jose Johnson Premkumar, Vladimir Vuskovic, Luna Dai, Daisuke Ikeda, Nihal Sandeep Balani, Jinna Lei, Mengmeng Niu, Hongjie Chai, Wangqing Yuan
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Patent number: 11354521Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.Type: GrantFiled: February 17, 2020Date of Patent: June 7, 2022Assignee: GOOGLE LLCInventors: James Kuczmarski, Vibhor Jain, Amarnag Subramanya, Nimesh Ranjan, Melvin Jose Johnson Premkumar, Vladimir Vuskovic, Luna Dai, Daisuke Ikeda, Nihal Sandeep Balani, Jinna Lei, Mengmeng Niu, Hongjie Chai, Wangqing Yuan
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Patent number: 11113481Abstract: Techniques described herein may serve to increase the language coverage of an automated assistant system, i.e. they may serve to increase the number of queries in one or more non-native languages for which the automated assistant is able to deliver reasonable responses. For example, techniques are described herein for training and utilizing a machine translation model to map a plurality of semantically-related natural language inputs in one language to one or more canonical translations in another language. In various implementations, the canonical translations may be selected and/or optimized for determining an intent of the speaker by the automated assistant, so that one or more responsive actions can be performed based on the speaker's intent. Put another way, the canonical translations may be specifically formatted for indicating the intent of the speaker to the automated assistant.Type: GrantFiled: May 2, 2019Date of Patent: September 7, 2021Assignee: GOOGLE LLCInventors: Melvin Jose Johnson Premkumar, Vladimir Vuskovic, James Kuczmarski, Hongjie Chai
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Publication number: 20210210076Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.Type: ApplicationFiled: March 24, 2021Publication date: July 8, 2021Inventors: James Kuczmarski, Vibhor Jain, Amarnag Subramanya, Nimesh Ranjan, Melvin Jose Johnson Premkumar, Vladimir Vuskovic, Luna Dai, Daisuke Ikeda, Nihal Sandeep Balani, Jinna Lei, Mengmeng Niu
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Patent number: 10984784Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.Type: GrantFiled: April 16, 2018Date of Patent: April 20, 2021Assignee: GOOGLE LLCInventors: James Kuczmarski, Vibhor Jain, Amarnag Subramanya, Nimesh Ranjan, Melvin Jose Johnson Premkumar, Vladimir Vuskovic, Luna Dai, Daisuke Ikeda, Nihal Sandeep Balani, Jinna Lei, Mengmeng Niu
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Publication number: 20210064828Abstract: Techniques described herein may serve to increase the language coverage of an automated assistant system, i.e. they may serve to increase the number of queries in one or more non-native languages for which the automated assistant is able to deliver reasonable responses. For example, techniques are described herein for training and utilizing a machine translation model to map a plurality of semantically-related natural language inputs in one language to one or more canonical translations in another language. In various implementations, the canonical translations may be selected and/or optimized for determining an intent of the speaker by the automated assistant, so that one or more responsive actions can be performed based on the speaker's intent. Put another way, the canonical translations may be specifically formatted for indicating the intent of the speaker to the automated assistant.Type: ApplicationFiled: May 2, 2019Publication date: March 4, 2021Inventors: Melvin Jose Johnson Premkumar, Vladimir Vuskovic, James Kuczmarski, Hongjie Chai
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Publication number: 20200320984Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.Type: ApplicationFiled: April 16, 2018Publication date: October 8, 2020Inventors: James Kuczmarski, Vibhor Jain, Amarnag Subramanya, Nimesh Ranjan, Melvin Jose Johnson Premkumar, Vladimir Vuskovic, Luna Dai, Daisuke Ikeda, Nihal Sandeep Balani, Jinna Lei, Mengmeng Niu
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Publication number: 20200184158Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.Type: ApplicationFiled: February 17, 2020Publication date: June 11, 2020Inventors: James Kuczmarski, Vibhor Jain, Amarnag Subramanya, Nimesh Ranjan, Melvin Jose Johnson Premkumar, Vladimir Vuskovic, Luna Dai, Daisuke Ikeda, Nihal Sandeep Balani, Jinna Lei, Mengmeng Niu, Hongjie Chai, Wangqing Yuan