Adaptive Noise Reduction of Speech Signals


We propose a new adaptive speech noise removal algorithm based on a twostage Wiener ltering. A rst Wiener lter is used to produce a smoothed estimate of the a priori signal-to-noise ratio (SNR), aided by a classi er that separates speech from noise frames, and a second Wiener lter is used to generate the nal output. Spectral analysis and synthesis is performed by a modulated complex lapped transform (MCLT). For noisy speech at a low 10 dB input SNR, for example, the proposed algorithm can achieve on average about 13 dB noise-to-mask ratio (NMR) reduction, or about 6 dB SNR improvement.

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@inproceedings{Jiang2000AdaptiveNR, title={Adaptive Noise Reduction of Speech Signals}, author={Wenqing Jiang and Henrique S. Malvar}, year={2000} }