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公开(公告)号：US12061861B2
公开(公告)日：2024-08-13
申请号：US17815211
申请日：2022-07-26
Applicant: Microsoft Technology Licensing, LLC
Inventor： Wei Liu , Padma Varadharajan , Piyush Behre , Nicholas Kibre , Edward C. Lin , Shuangyu Chang , Che Zhao , Khuram Shahid , Heiko Willy Rahmel
IPC: G06F40/284 , G06F40/117 , G06F40/151 , G06F40/166
CPC classification number: G06F40/151 , G06F40/117 , G06F40/166 , G06F40/284
Abstract: Solutions for custom display post processing (DPP) in speech recognition (SR) use a customized multi-stage DPP pipeline that transforms a stream of SR tokens from lexical form to display form. A first transformation stage of the DPP pipeline receives the stream of tokens, in turn, by an upstream filter, a base model stage, and a downstream filter, and transforms a first aspect of the stream of tokens (e.g., disfluency, inverse text normalization (ITN), capitalization, etc.) from lexical form into display form. The upstream filter and/or the downstream filter alter the stream of tokens to change the default behavior of the DPP pipeline into custom behavior. Additional transformation stages of the DPP pipeline perform further transforms, allowing for outputting final text in a display format that is customized for a specific user. This permits each user to efficiently leverage a common baseline DPP pipeline to produce a custom output.
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公开(公告)号：US20210304769A1
公开(公告)日：2021-09-30
申请号：US15931788
申请日：2020-05-14
Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor： Guoli Ye , Yan Huang , Wenning Wei , Lei He , Eva Sharma , Jian Wu , Yao Tian , Edward C. Lin , Yifan Gong , Rui Zhao , Jinyu Li , William Maxwell Gale
Abstract: Systems, methods, and devices are provided for generating and using text-to-speech (TTS) data for improved speech recognition models. A main model is trained with keyword independent baseline training data. In some instances, acoustic and language model sub-components of the main model are modified with new TTS training data. In some instances, the new TTS training is obtained from a multi-speaker neural TTS system for a keyword that is underrepresented in the baseline training data. In some instances, the new TTS training data is used for pronunciation learning and normalization of keyword dependent confidence scores in keyword spotting (KWS) applications. In some instances, the new TTS training data is used for rapid speaker adaptation in speech recognition models.
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公开(公告)号：US11587569B2
公开(公告)日：2023-02-21
申请号：US15931788
申请日：2020-05-14
Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor： Guoli Ye , Yan Huang , Wenning Wei , Lei He , Eva Sharma , Jian Wu , Yao Tian , Edward C. Lin , Yifan Gong , Rui Zhao , Jinyu Li , William Maxwell Gale
Abstract: Systems, methods, and devices are provided for generating and using text-to-speech (TTS) data for improved speech recognition models. A main model is trained with keyword independent baseline training data. In some instances, acoustic and language model sub-components of the main model are modified with new TTS training data. In some instances, the new TTS training is obtained from a multi-speaker neural TTS system for a keyword that is underrepresented in the baseline training data. In some instances, the new TTS training data is used for pronunciation learning and normalization of keyword dependent confidence scores in keyword spotting (KWS) applications. In some instances, the new TTS training data is used for rapid speaker adaptation in speech recognition models.
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公开(公告)号：US12205596B2
公开(公告)日：2025-01-21
申请号：US18108316
申请日：2023-02-10
Applicant: Microsoft Technology Licensing, LLC
Inventor： Guoli Ye , Yan Huang , Wenning Wei , Lei He , Eva Sharma , Jian Wu , Yao Tian , Edward C. Lin , Yifan Gong , Rui Zhao , Jinyu Li , William Maxwell Gale
Abstract: Systems, methods, and devices are provided for generating and using text-to-speech (TTS) data for improved speech recognition models. A main model is trained with keyword independent baseline training data. In some instances, acoustic and language model sub-components of the main model are modified with new TTS training data. In some instances, the new TTS training is obtained from a multi-speaker neural TTS system for a keyword that is underrepresented in the baseline training data. In some instances, the new TTS training data is used for pronunciation learning and normalization of keyword dependent confidence scores in keyword spotting (KWS) applications. In some instances, the new TTS training data is used for rapid speaker adaptation in speech recognition models.
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