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Speech Enhancement Based on Improved Minima Controlled Recursive Averaging Incorporating GSAP  

Song, Ji-Hyun ((Department of Electronic Engineering, Inha University)
Bang, Dong-Hyeouck ((Department of Electronic Engineering, Inha University)
Lee, Sang-Min ((Department of Electronic Engineering, Inha University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.49, no.1, 2012 , pp. 104-111 More about this Journal
Abstract
In this paper, we propose a novel method to improve the performance of the improved minima controlled recursive averaging (IMCRA). From an examination for various noise environment, it is shown that the IMCRA has a fundamental drawback for the noise power estimate at the offset region of continuity speech signals. Espectially, it is difficult to obtain the robust estimates of the noise power in non-stationary noisy environments that is rapidly changed the spectral characteristics such as babble noise. To overcome the drawback, we apply the global speech absence probability (GSAP) conditioned on both a priori SNR and a posteriori SNR to the speech detection algorithm of IMCRA. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and a composite measure test, we show that the proposed algorithm yields better results compared to the conventional IMCRA-based scheme under various noise environments. In particular, in the case of babble 5 dB, the proposed method produced a remarkable improvement compared to the IMCRA ( PESQ = 0.026, composite measure = 0.029 ).
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