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公开(公告)号:US11043214B1
公开(公告)日:2021-06-22
申请号:US16204670
申请日:2018-11-29
Applicant: Amazon Technologies, Inc.
Inventor: Behnam Hedayatnia , Anirudh Raju , Ankur Gandhe , Chandra Prakash Khatri , Ariya Rastrow , Anushree Venkatesh , Arindam Mandal , Raefer Christopher Gabriel , Ahmad Shikib Mehri
Abstract: Described herein is a system for rescoring automatic speech recognition hypotheses for conversational devices that have multi-turn dialogs with a user. The system leverages dialog context by incorporating data related to past user utterances and data related to the system generated response corresponding to the past user utterance. Incorporation of this data improves recognition of a particular user utterance within the dialog.
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公开(公告)号:US11194973B1
公开(公告)日:2021-12-07
申请号:US16363363
申请日:2019-03-25
Applicant: Amazon Technologies, Inc.
Inventor: Rahul Goel , Chandra Prakash Khatri , Tagyoung Chung , Raefer Christopher Gabriel , Anushree Venkatesh , Behnam Hedayatnia , Sanghyun Yi
IPC: G06F40/35 , G10L15/26 , G06F40/289 , H04L12/58 , G06N20/00
Abstract: A system that can engage in a dialog with a user may select a system response to a user input based on how the system estimates a user may respond to a potential system response. Models may be trained to evaluate a potential system response in view of various available data including dialog history, entity data, etc. Each model may score the potential system response for various qualitative aspects such as whether the response is likely to be comprehensible, on-topic, interesting, likely to lead to the dialog continuing, etc. Such scores may be combined to other scores such as whether the potential response is coherent or engaging. The models may be trained using previous dialog/chatbot evaluation data. At runtime the scores may be used to select a system response to a user input as part of the dialog.
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公开(公告)号:US20210312914A1
公开(公告)日:2021-10-07
申请号:US17340378
申请日:2021-06-07
Applicant: Amazon Technologies, Inc.
Inventor: Behnam Hedayatnia , Anirudh Raju , Ankur Gandhe , Chandra Prakash Khatri , Ariya Rastrow , Anushree Venkatesh , Arindam Mandal , Raefer Christopher Gabriel , Ahmad Shikib Mehri
Abstract: Described herein is a system for rescoring automatic speech recognition hypotheses for conversational devices that have multi-turn dialogs with a user. The system leverages dialog context by incorporating data related to past user utterances and data related to the system generated response corresponding to the past user utterance. Incorporation of this data improves recognition of a particular user utterance within the dialog.
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