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http://dx.doi.org/10.7776/ASK.2011.30.3.123

Improved Minimum Statistics Based on Environment-Awareness for Noise Power Estimation  

Son, Young-Ho (인하대학교 전자공학부)
Choi, Jae-Hun (인하대학교 전자공학부)
Chang, Joon-Hyuk (한양대학교 융합전자공학부)
Publication Information
The Journal of the Acoustical Society of Korea / v.30, no.3, 2011 , pp. 123-128 More about this Journal
Abstract
In this paper, we propose the improved noise power estimation in speech enhancement under various noise environments. The previous MS algorithm tracking the minimum value of finite search window uses the optimal power spectrum of signal for smoothing and adopts minimum probability. From the investigation of the previous MS-based methods it can be seen that a fixed size of the minimum search window is assumed regardless of the various environment. To achieve the different search window size, we use the noise classification algorithm based on the Gaussian mixture model (GMM). Performance of the proposed enhancement algorithm is evaluated by ITU-T P.862 perceptual evaluation of speech quality (PESQ) under various noise environments. Based on this, we show that the proposed algorithm yields better result compared to the conventional MS method.
Keywords
Minimum Statistics (MS); Gaussian mixture model (GMM); Environment-awareness;
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