Robust Voice Activity Detection Based on Discrete Wavelet Transform
نویسنده
چکیده
This paper mainly addresses the problem of determining voice activity in presence of noise, especially in a dynamically varying background noise. The proposed voice activity detection algorithm is based on structure of three-layer wavelet decomposition. Appling auto-correlation function into each subband exploits the fact that intensity of periodicity is more significant in sub-band domain than that in full-band domain. In addition, Teager energy operator (TEO) is used to eliminate the noise components from the wavelet coefficients on each subband. Experimental results show that the proposed wavelet-based algorithm is prior to others and can work in a dynamically varying background noise.
منابع مشابه
A New Algorithm for Voice Activity Detection Based on Wavelet Packets (RESEARCH NOTE)
Speech constitutes much of the communicated information; most other perceived audio signals do not carry nearly as much information. Indeed, much of the non-speech signals maybe classified as ‘noise’ in human communication. The process of separating conversational speech and noise is termed voice activity detection (VAD). This paper describes a new approach to VAD which is based on the Wavelet ...
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