A Comparison of Noise Reduction Techniques for Robust Speech Recognition

Abstract

. This report presents the integration of several noise reduction methods into the frontend for speech recognition developed at IDIAP. The chosen methods are : Spectral Subtraction, Cepstral Mean Subtraction and Blind Equalization. These dierent methods are studied from a theoretical point of view. Their implementation is described and they are tested on the Numbers95 speech database. A good noise robustness is obtained by combining two of these methods, like Spectral Subtraction with Cepstral Mean Subtraction or Spectral Subtraction with Blind Equalization. The later combination is found to be more appropriate for real recognition systems since it is frame synchronous. A comparison with Jah-RASTA-PLP is also given. Acknowledgements: The support of the OFES under the grant for the \Speech, Hearing and Recognition" (SPHEAR) project # OFES 970299 is gratefully acknowledged. The work described in this report beneted from fruitful discussions with Chac Mokbel. IDIAP{RR 99-10 1 Content..