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公开(公告)号：US20230177264A1
公开(公告)日：2023-06-08
申请号：US18103277
申请日：2023-01-30
申请人： GOOGLE LLC
发明人： David Kogan , Wangqing Yuan , Guanglei Wang , Vincent Lacey , Wei Chen , Shaun Post
IPC分类号： G06F40/263 , G06F40/279 , G06F3/0482 , G10L15/19
CPC分类号： G06F40/263 , G06F3/0482 , G06F40/279 , G10L15/19
摘要： Implementations relate to determining a secondary language proficiency measure, for a user in a secondary language (i.e., a language other than a primary language specified for the user), where determining the secondary language proficiency measure is based on past interactions of the user that are related to the secondary language. Those implementations further relate to utilizing the determined secondary language proficiency measure to increase efficiency of user interaction(s), such as interaction(s) with a language learning application and/or an automated assistant. Some of those implementations utilize the secondary language proficiency measure in automatically setting value(s), biasing automatic speech recognition, and/or determining how to render natural language output.
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公开(公告)号：US20230084294A1
公开(公告)日：2023-03-16
申请号：US17475897
申请日：2021-09-15
申请人： GOOGLE LLC
摘要： Implementations relate to determining multilingual content to render at an interface in response to a user submitted query. Those implementations further relate to determining a first language response and a second language response to a query that is submitted to an automated assistant. Some of those implementations relate to determining multilingual content that includes a response to the query in both the first and second languages. Other implementations relate to determining multilingual content that includes a query suggestion in the first language and a query suggestion in a second language. Some of those implementations relate to pre-fetching results for the query suggestions prior to rendering the multilingual content.
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公开(公告)号：US11354521B2
公开(公告)日：2022-06-07
申请号：US16792572
申请日：2020-02-17
申请人： Google LLC
发明人： 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
IPC分类号： G06F40/00 , G06F40/58 , G06F40/47 , G06F16/33 , G06K9/62 , H04L51/02 , G06N20/00 , G06F16/332
摘要： 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.
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4.发明申请公开(公告)号：US20200104746A1
公开(公告)日：2020-04-02
申请号：US16611725
申请日：2018-12-14
申请人： Google LLC
发明人： Brian Strope , Yun-hsuan Sung , Wangqing Yuan
IPC分类号： G06N20/00 , G06F16/33 , G06F16/35 , G06F16/332 , G06N5/04
摘要： Systems, methods, and computer readable media related to: training an encoder model that can be utilized to determine semantic similarity of a natural language textual string to each of one or more additional natural language textual strings (directly and/or indirectly); and/or using a trained encoder model to determine one or more responsive actions to perform in response to a natural language query. The encoder model is a machine learning model, such as a neural network model. In some implementations of training the encoder model, the encoder model is trained as part of a larger network architecture trained based on one or more tasks that are distinct from a “semantic textual similarity” task for which the encoder model can be used.
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公开(公告)号：US20190074010A1
公开(公告)日：2019-03-07
申请号：US16181874
申请日：2018-11-06
申请人： Google LLC
发明人： Bryan Horling , David Kogan , Maryam Garrett , Daniel Kunkle , Wan Fen Nicole Quah , Ruijie He , Wangqing Yuan , Wei Chen , Michael Itz
CPC分类号： G10L15/22 , G06F16/9535 , G10L15/1815 , G10L15/26 , G10L15/30
摘要： Techniques are described herein for chatbots to achieve greater social grace by tracking users' states and providing corresponding dialog. In various implementations, input may be received from a user at a client device operating a chatbot, e.g., during a first session between the user and the chatbot. The input may be semantically processed to determine a state expressed by the user to the chatbot. An indication of the state expressed by the user may be stored in memory for future use by the chatbot. It may then be determined, e.g., by the chatbot based on various signals, that a second session between the user and the chatbot is underway. In various implementations, as part of the second session, the chatbot may output a statement formed from a plurality of candidate words, phrases, and/or statements based on the stored indication of the state expressed by the user.
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6.发明公开公开(公告)号：US20240311585A1
公开(公告)日：2024-09-19
申请号：US18673145
申请日：2024-05-23
申请人： GOOGLE LLC
发明人： Wangqing Yuan , David Kogan , Vincent Lacey , Guanglei Wang , Shaun Post , Bryan Christopher Horling , Michael Anthony Schuler
IPC分类号： G06F40/51 , G06F40/211 , G06F40/289
CPC分类号： G06F40/51 , G06F40/211 , G06F40/289
摘要： Implementations relate to determining a well-formed phrase to suggest to a user to submit in lieu of a not well-formed phrase. The suggestion is rendered via an interface that is provided to a client device of the user. Those implementations relate to determining that a phrase is not well-formed, identifying alternate phrases that are related to the not well-formed phrase, and scoring the alternate phrases to select one or more of the alternate phrases to render via the interface. Some of those implementations are related to identifying that the phrase is not well-formed based on occurrences of the phrase in documents that are generated by a source with the language of the phrase as the primary language of the creator.
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公开(公告)号：US11942082B2
公开(公告)日：2024-03-26
申请号：US17825778
申请日：2022-05-26
申请人： GOOGLE LLC
发明人： 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
IPC分类号： G06F40/47 , G06F16/33 , G06F16/332 , G06F18/22 , G06F40/58 , G06N20/00 , G10L15/00 , G10L15/183 , G10L15/22 , H04L51/02
CPC分类号： G10L15/183 , G06F16/3329 , G06F16/3337 , G06F18/22 , G06F40/47 , G06F40/58 , G06N20/00 , G10L15/005 , G10L15/22 , H04L51/02
摘要： 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.
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公开(公告)号：US20230394049A1
公开(公告)日：2023-12-07
申请号：US18236285
申请日：2023-08-21
申请人： GOOGLE LLC
发明人： David Kogan , Wangqing Yuan , Wei Chen , Bryan Horling , Michael Itz
IPC分类号： G06F16/2457 , G06N20/00 , G06F16/332 , G06F40/169 , H04L51/216 , G10L15/22 , H04L51/02 , H04W4/14
CPC分类号： G06F16/24578 , G06N20/00 , G06F16/3329 , H04W4/14 , H04L51/216 , G10L15/22 , H04L51/02 , G06F40/169
摘要： Methods, apparatus, systems, and computer-readable media are provided for automatically augmenting message exchange threads based on a detected tone of messages exchanged between participants. In various implementations, a message contributed to a message exchange thread involving one or more message exchange clients by a participant may be determined. In various implementations, an idle chatter score associated with the message may be calculated. In various implementations, either a conversational response to the message or content responsive to a search query generated based on the message may be selectively incorporated into the message exchange thread based at least in part on the idle chatter score. In some implementations, a search query suitability score associated with the message may also be calculated.
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公开(公告)号：US11568139B2
公开(公告)日：2023-01-31
申请号：US17351861
申请日：2021-06-18
申请人： GOOGLE LLC
发明人： David Kogan , Wangqing Yuan , Guanglei Wang , Vincent Lacey , Wei Chen , Shaun Post
IPC分类号： G06F40/263 , G06F3/0482 , G10L15/19 , G06F40/279
摘要： Implementations relate to determining a secondary language proficiency measure, for a user in a secondary language (i.e., a language other than a primary language specified for the user), where determining the secondary language proficiency measure is based on past interactions of the user that are related to the secondary language. Those implementations further relate to utilizing the determined secondary language proficiency measure to increase efficiency of user interaction(s), such as interaction(s) with a language learning application and/or an automated assistant. Some of those implementations utilize the secondary language proficiency measure in automatically setting value(s), biasing automatic speech recognition, and/or determining how to render natural language output.
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公开(公告)号：US20220284198A1
公开(公告)日：2022-09-08
申请号：US17825778
申请日：2022-05-26
申请人： GOOGLE LLC
发明人： 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
摘要： 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.
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