LOG-SPECTRAL AMPLITUDE ESTIMATION WITH GENERALIZED GAMMA DISTRIBUTIONS FOR SPEECH ENHANCEMENT

被引：0
|
作者：
Borgstroem, Bengt J. [1 ]
Alwan, Abeer [1 ]
机构：
[1] Univ Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90024 USA
来源：
2011 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING | 2011年
关键词：
Speech Enhancement; Log-spectral Amplitude Estimator; Generalized Gamma Distribution; SQUARE ERROR ESTIMATION;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
This paper presents a family of log-spectral amplitude (LSA) estimators for speech enhancement. Generalized Gamma distributed (GGD) priors are assumed for speech short-time spectral amplitudes (STSAs), providing mathematical flexibility in capturing the statistical behavior of speech. Although solutions are not obtainable in closed-form, estimators are expressed as limits, and can be efficiently approximated. When applied to the Noizeus database [1], proposed estimators are shown to provide improvements in segmental signal-to-noise ratio (SSNR) and COSH distance [2], relative to the LSA estimator proposed by Ephraim and Malah [3].
引用
收藏
页码：4756 / 4759
页数：4
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