Denoising Using Optimized Wavelet Filtering for Automatic Speech Recognition

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.