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Speaker Adaptation Based on PARAFAC2 of Transformation Matrices for Continuous Speech Recognition

机译:基于PARAFAC2变换矩阵的说话人自适应用于连续语音识别

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摘要

We present an acoustic model adaptation method where the transformation matrix for a new speaker is given by the product of bases and a weight matrix. The bases are built from the parallel factor analysis 2 (PARAFAC2) of training speakers' transformation matrices. We perform continuous speech recognition experiments using the WSJO corpus.
机译:我们提出了一种声学模型自适应方法,其中,新扬声器的变换矩阵由基数和权重矩阵的乘积给出。该基础是根据培训演讲者的转换矩阵的并行因子分析2(PARAFAC2)建立的。我们使用WSJO语料库进行连续的语音识别实验。

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