For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Noise Estimation for Speech Enhancement Based on Quasi-Gaussian Distributed Power Spectrum Series by Radical Root Transformation
Tian YE Yasunari YOKOTA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2017/06/01
Online ISSN: 1745-1337
Type of Manuscript: PAPER
Category: Information Theory
power spectrum series, quasi-Gaussian distribution, speech activity detector, radical root transformation,
Full Text: PDF(10.6MB)
>>Buy this Article
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.