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Traditional noise reduction methods usually are based on the assumption that the short-term statistical distributions of speech and noise are different. Differently from that assumption, we have proposed a noise reduction method based on the assumption that the temporal modulations of noise and speech are different. Two steps are used in the proposed algorithm: one is the temporal modulation contrast...
In this paper, we proposed a robust speech feature extraction algorithm for automatic speech recognition which reduced the noise effect in the temporal modulation domain. The proposed algorithm has two steps to deal with the time series of cepstral coefficients. The first step adopted a modulation contrast normalization to normalize the temporal modulation contrast of both clean and noisy speech to...
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