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Noise-robust speech recognition by discriminative adaptation in parallel model combination

机译:并行模型组合中判别自适应的鲁棒语音识别

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摘要

A discriminative adaptation method for parallel model combination (PMC) is proposed. For the adaptation, a modified version of PMC is adopted and the association factor defined in this variant is discriminatively adapted based on the generalised probabilistic descent (GPD) method. The proposed method is shown to be very effective at improving the recognition performances under extreme noise conditions with a small amount of adaptation data.
机译:提出了一种适用于并行模型组合的判别式自适应方法。为了进行修改,采用了PMC的修改版本,并且基于广义概率下降(GPD)方法对本变量中定义的关联因子进行了区分性修改。所提出的方法显示出在具有少量自适应数据的情况下,在提高极端噪声条件下的识别性能方面非常有效。

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