Kannu Mehta

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In this paper, we present a robust feature extraction algorithm based on auditory periphery model for Speech Recognition. At the front-end, a normalized filter bank based on Gammatone filtering is applied to the speech spectra followed by a power law non-linearity. Experiments show that the proposed features named as EFCCs (ERB scale cepstral coefficients)(More)
In this paper, we propose a robust voice activity detection method based on long-term stationarity (LTS) of the speech signal. The approach is motivated by the fact that noise, in timedomain, is relatively more stationary as compared to speech. We describe the use of Linear dynamic models (LDMs) as a measure of calculating the long-term stationarity of the(More)
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