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Context-dependent acoustic models for speech recognition with eigenvoice training
Context-dependent acoustic models for speech recognition with eigenvoice training
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机译:特征语音训练用于语音识别的上下文相关声学模型
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摘要
A reduced dimensionality eigenvoice analytical technique is used during training to develop context-dependent acoustic models fcr allophones. The eigenvoice technique is also used during run time upon the speech of a new speaker. The technique removes individual speaker idiosyncrasies, to produce more universally applicable and robust allophone models. In one embodiment the eigenvoice technique is used to identify the centroid of each speaker, which may then be "subtracted out" of the recognition equation. In another embodiment maximum likelihood estimation techniques are used to develop common decision tree frameworks that may be shared across all speakers when constructing the eigenvoice representation of speaker space.
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