Abstract
In this paper, we investigate the enhancement of speech by applying kernel adaptive filter. Noise removal is very important in many applications like telephone conversation, speech recognition, etc. Kernel methods have shown good results for other applications like handwriting recognition, inverse distance weightings, etc. To improve the speech quality and intelligibility, we can process the signals in new domain like Reproducing Kernel Hilbert Space (RKHS) unlike time and frequency domains. We have used the noisy speech corpus (NOIZEUS) for the experiments. The experimental results shown the noise removal in RKHS has good improvement in the Signal to Noise Ratio (SNR) values as compared the traditional methods.
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