An Improved Speech Absence Probability Estimation based on Environmental Noise Classification

환경잡음분류 기반의 향상된 음성부재확률 추정

  • Received : 2011.06.25
  • Accepted : 2011.08.29
  • Published : 2011.10.31


In this paper, we propose a improved speech absence probability estimation algorithm by applying environmental noise classification for speech enhancement. The previous speech absence probability required to seek a priori probability of speech absence was derived by applying microphone input signal and the noise signal based on the estimated value of a posteriori SNR threshold. In this paper, the proposed algorithm estimates the speech absence probability using noise classification algorithm which is based on Gaussian mixture model in order to apply the optimal parameter each noise types, unlike the conventional fixed threshold and smoothing parameter. Performance of the proposed enhancement algorithm is evaluated by ITU-T P.862 PESQ (perceptual evaluation of speech quality) and composite measure under various noise environments. It is verified that the proposed algorithm yields better results compared to the conventional speech absence probability estimation algorithm.


Speech absence probability;Gaussian mixture model (GMM);Noise Classification


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