IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Regular Section
Noise Estimation for Speech Enhancement Based on Quasi-Gaussian Distributed Power Spectrum Series by Radical Root Transformation
Tian YEYasunari YOKOTA
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2017 Volume E100.A Issue 6 Pages 1306-1314

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Abstract

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.

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© 2017 The Institute of Electronics, Information and Communication Engineers
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