一篇利用隐马尔可夫模型进行静音检测的好文章
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Voice activity detection based on multiple statistical modelsIEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 54, NO. 6, JUNE 2006
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Voice Activity Detection Based on Multiple Statistical Models
Joon-Hyuk Chang, Member, IEEE, Nam Soo Kim, Member, IEEE, and Sanjit K. Mitra, Life Fellow, IEEE
Abstract―One of the key issues in practical speech processing is to achieve robust voice activity detection (VAD) against the background noise. Most of the statistical model-based approaches have tried to employ the Gaussian assumption in the discrete Fourier transform (DFT) domain, which, however, deviates from the real observation. In this paper, we propose a class of VAD algorithms based on several statistical models. In addition to the Gaussian model, we also incorporate the complex Laplacian and Gamma probability density functions to our analysis of statist
1965
Voice Activity Detection Based on Multiple Statistical Models
Joon-Hyuk Chang, Member, IEEE, Nam Soo Kim, Member, IEEE, and Sanjit K. Mitra, Life Fellow, IEEE
Abstract―One of the key issues in practical speech processing is to achieve robust voice activity detection (VAD) against the background noise. Most of the statistical model-based approaches have tried to employ the Gaussian assumption in the discrete Fourier transform (DFT) domain, which, however, deviates from the real observation. In this paper, we propose a class of VAD algorithms based on several statistical models. In addition to the Gaussian model, we also incorporate the complex Laplacian and Gamma probability density functions to our analysis of statist
关键词： Voice activity detection based multiple statistical models
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