Noise Reduction Algorithms for Speech Enhancement
Date Issued
2011
Date
2011
Author(s)
Huang, Chung-Han
Abstract
When clean speech affected by various types of noise, there are many methods to reduce noise. Companying more noise we reduce, more speech distortions the enhanced signals produce. Although wiener filter makes mean square error minimum(MMSE), it also has highly speech distortions. The thesis improves wiener filter to become a tradeoff filter and implements adaptive tradeoff parameter to let it have different degree of suppression in different SNR. We also improve the wiener filter with different gain function in order to make a balance between noise reduction and speech distortion, and it saves some information of clean speech. Besides, a new noise estimation method originated from minimum statistical estimation is proposed. All of the improvement methods will reduce distortion of speech and maintain a certain degree of noise reduction. At last we compare result of the improved algorithms with conventional wiener filter in white noise, babble noise and Vuvuzela noise based on speech distortion measure and noise reduction measure.
Subjects
noise reduction
speech distortion
MMSE
wiener filter
noise estimation
Type
thesis
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