Invention Grant
US08306819B2 Enhanced automatic speech recognition using mapping between unsupervised and supervised speech model parameters trained on same acoustic training data
有权
使用在相同声学训练数据上训练的无监督和受监督的语音模型参数之间的映射来增强自动语音识别
- Patent Title: Enhanced automatic speech recognition using mapping between unsupervised and supervised speech model parameters trained on same acoustic training data
- Patent Title (中): 使用在相同声学训练数据上训练的无监督和受监督的语音模型参数之间的映射来增强自动语音识别
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Application No.: US12400528Application Date: 2009-03-09
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Publication No.: US08306819B2Publication Date: 2012-11-06
- Inventor: Chaojun Liu , Yifan Gong
- Applicant: Chaojun Liu , Yifan Gong
- Applicant Address: US WA Redmond
- Assignee: Microsoft Corporation
- Current Assignee: Microsoft Corporation
- Current Assignee Address: US WA Redmond
- Agency: Lee & Hayes, PLLC
- Main IPC: G10L15/06
- IPC: G10L15/06 ; G10L15/00
Abstract:
Techniques for enhanced automatic speech recognition are described. An enhanced ASR system may be operative to generate an error correction function. The error correction function may represent a mapping between a supervised set of parameters and an unsupervised training set of parameters generated using a same set of acoustic training data, and apply the error correction function to an unsupervised testing set of parameters to form a corrected set of parameters used to perform speaker adaptation. Other embodiments are described and claimed.
Public/Granted literature
- US20100228548A1 TECHNIQUES FOR ENHANCED AUTOMATIC SPEECH RECOGNITION Public/Granted day:2010-09-09
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