Noise Estimation for Speech Enhancement Based on Quasi-Gaussian Distributed Power Spectrum Series by Radical Root Transformation

Tian YE  Yasunari YOKOTA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E100-A   No.6   pp.1306-1314
Publication Date: 2017/06/01
Online ISSN: 1745-1337
Type of Manuscript: PAPER
Category: Information Theory
Keyword: 
power spectrum series,  quasi-Gaussian distribution,  speech activity detector,  radical root transformation,  

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Summary: 
This contribution presents and analyzes the statistical regularity related to the noise power spectrum series and the speech spectrum series. It also undertakes a thorough inquiry of the quasi-Gaussian distributed power spectrum series obtained using the radical root transformation. Consequently, a noise-estimation algorithm is proposed for speech enhancement. This method is effective for separating the noise power spectrum from the noisy speech power spectrum. In contrast to standard noise-estimation algorithms, the proposed method requires no speech activity detector. It was confirmed to be conceptually simple and well suited to real-time implementations. Practical experiment tests indicated that our method is preferred over previous methods.