Denoising Using Optimized Wavelet Filtering for Automatic Speech Recognition

被引：0

作者：

Gomez, Randy ^{[1
]}

Kawahara, Tatsuya ^{[1
]}

机构：

[1] Kyoto Univ, ACCMS, Sakyo Ku, Kyoto 6068501, Japan

来源：

12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5 | 2011年

关键词：

Speech recognition; Robustness; Denoising and Wavelet;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present an improved denoising method based on filtering of the noisy wavelet coefficients using a Wiener gain for automatic speech recognition (ASR). We optimize the wavelet parameters for speech and different noise profiles to achieve a better estimate of the Wiener gain for effective filtering. Moreover, we introduce a scaling parameter in the Wiener gain to minimize mismatch caused by distortion during the denoising process. Experimental results in large vocabulary continuous speech recognition (LVCSR) show that the proposed method is effective and robust to different noise conditions.

引用

页码：1684 / 1687

页数：4

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