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An Improved Speech Absence Probability Estimation based on Environmental Noise Classification
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 Title & Authors
An Improved Speech Absence Probability Estimation based on Environmental Noise Classification
Son, Young-Ho; Park, Yun-Sik; An, Hong-Sub; Lee, Sang-Min;
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 Abstract
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.
 Keywords
Speech absence probability;Gaussian mixture model (GMM);Noise Classification;
 Language
Korean
 Cited by
1.
국가기록원 음성 기록물의 복원과 분석,오세진;강홍구;

한국음향학회지, 2013. vol.32. 3, pp.269-278 crossref(new window)
1.
Restoration for Speech Records Managed by the National Archives of Korea, The Journal of the Acoustical Society of Korea, 2013, 32, 3, 269  crossref(new windwow)
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