We present a new method for noisy speech recognition, which combines multiple timescale analysis with sub band method.
本文根据多时间尺度分析与子带方法，提出了一种多时间尺度复合子带的噪声环境下语音识别新方法。
The conventional sub-band methods can improve the recognition accuracy of noisy speech, but degrade that of clean speech.
传统的子带特征方法虽然能提高噪声下的语音识别性能，但通常会使无噪声情况下的识别性能下降。
Based on local signal to noise ratio, the method estimates characteristic component of speech sound sub band covered by noise.
一种根据局部信噪比，估计受噪声掩蔽的语音子带特征分量的方法。
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