Modulation Domain Spectral Subtraction for Speech Enhancement

被引:0
|
作者
Paliwal, Kuldip [1 ]
Schwerin, Belinda [1 ]
Wojcicki, Kamil [1 ]
机构
[1] Griffith Univ, Signal Proc Lab, Nathan, Qld 4111, Australia
关键词
speech enhancement; spectral subtraction; modulation domain; analysis-modification-synthesis (AMS);
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we investigate the modulation domain as an alternative to the acoustic domain for speech enhancement. More specifically, we wish to determine how competitive the modulation domain is for spectral subtraction as compared to the acoustic domain. For this purpose, we extend the traditional analysis-modification-synthesis framework to include modulation domain processing. We then compensate the noisy modulation spectrum for additive noise distortion by applying the spectral subtraction algorithm in the modulation domain. Using subjective listening tests and objective speech quality evaluation we show that the proposed method results in improved speech quality. Furthermore, applying spectral subtraction in the modulation domain does not introduce the musical noise artifacts that are typically present after acoustic domain spectral subtraction. The proposed method also achieves better background noise reduction than the MMSE method.
引用
收藏
页码:1343 / 1346
页数:4
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