公开(公告)号：US11087748B2

公开(公告)日：2021-08-10

申请号：US15977699

申请日：2018-05-11

Applicant: Google LLC

Inventor： Gleb Skobeltsyn ,  Mihaly Kozsevnyikov ,  Vladimir Vuskovic

IPC: G10L15/18 ,  G06F3/16 ,  G10L15/22 ,  G06F40/30

Abstract: The systems and methods of the present disclosure generally relate to a data processing system that can identify and surface alternative requests when presented with ambiguous, unclear, or other requests to which a data processing system may not be able to respond. The data processing system can improve the efficiency of network transmissions to reduce network bandwidth usage and processor utilization by selecting alternative requests that are responsive to the intent of the original request.

公开(公告)号：US20210210076A1

公开(公告)日：2021-07-08

申请号：US17211488

申请日：2021-03-24

Applicant: Google LLC

Inventor： 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

IPC: G10L15/183 ,  G10L15/00 ,  G10L15/22

Abstract: 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.

公开(公告)号：US10984784B2

公开(公告)日：2021-04-20

申请号：US16082175

申请日：2018-04-16

Applicant: Google LLC

Inventor： 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

IPC: G10L15/00 ,  G10L15/183 ,  G10L15/22

Abstract: 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.

公开(公告)号：US20210064828A1

公开(公告)日：2021-03-04

申请号：US16621578

申请日：2019-05-02

Applicant: Google LLC

Inventor： Melvin Jose Johnson Premkumar ,  Vladimir Vuskovic ,  James Kuczmarski ,  Hongjie Chai

IPC: G06F40/58 ,  G10L15/22 ,  G10L15/06 ,  G10L19/008 ,  G06F40/51 ,  G06F40/30

Abstract: 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.

公开(公告)号：US20200320984A1

公开(公告)日：2020-10-08

申请号：US16082175

申请日：2018-04-16

Applicant: Google LLC

Inventor： 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

IPC: G10L15/183 ,  G10L15/22 ,  G10L15/00

Abstract: 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.

公开(公告)号：US20200227031A1

公开(公告)日：2020-07-16

申请号：US16829786

申请日：2020-03-25

Applicant: Google LLC

Inventor： Gleb Skobeltsyn ,  Mihaly Kozsevnyikov ,  Vladimir Vuskovic

IPC: G10L15/18 ,  G06F3/16 ,  G10L15/22 ,  G06F40/30

Abstract: The systems and methods of the present disclosure generally relate to a data processing system that can identify and surface alternative requests when presented with ambiguous, unclear, or other requests to which a data processing system may not be able to respond. The data processing system can improve the efficiency of network transmissions to reduce network bandwidth usage and processor utilization by selecting alternative requests that are responsive to the intent of the original request.

公开(公告)号：US20200184158A1

公开(公告)日：2020-06-11

申请号：US16792572

申请日：2020-02-17

Applicant: Google LLC

Inventor： 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: G06F40/58 ,  G06F40/47 ,  G06F16/33 ,  G06F16/332 ,  H04L12/58 ,  G06N20/00 ,  G06K9/62

Abstract: 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.

公开(公告)号：US10482882B2

公开(公告)日：2019-11-19

申请号：US15825919

申请日：2017-11-29

Applicant: Google LLC

Inventor： Vladimir Vuskovic ,  Stephan Wenger ,  Zineb Ait Bahajji ,  Martin Baeuml ,  Alexandru Dovlecel ,  Gleb Skobeltsyn

IPC: G10L15/22 ,  G06F17/27 ,  G10L15/18

Abstract: Methods, apparatus, and computer readable media are described related to automated assistants that proactively incorporate, into human-to-computer dialog sessions, unsolicited content of potential interest to a user. In various implementations, based on content of an existing human-to-computer dialog session between a user and an automated assistant, an entity mentioned by the user or automated assistant may be identified. Fact(s)s related to the entity or to another entity that is related to the entity may be identified based on entity data contained in database(s). For each of the fact(s), a corresponding measure of potential interest to the user may be determined. Unsolicited natural language content may then be generated that includes one or more of the facts selected based on the corresponding measure(s) of potential interest. The automated assistant may then incorporate the unsolicited content into the existing human-to-computer dialog session or a subsequent human-to-computer dialog session.