SPEECH ENHANCEMENT USING NONNEGATIVE MATRIX FACTORIZATION WITH TEMPORAL CONTINUITY

被引：0
|
作者：
Nam, Seung-Hyon [1 ]
机构：
[1] Paichai Univ, Dept Elect Engn, 155-40,Baejae Ro, Daejeon 303735, South Korea
来源：
JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA | 2015年 / 34卷 / 03期
关键词：
Speech enhancement; Nonnegative matrix factorization; Variational Bayesian inference; Gamma-Makov chain; Temporal continuity;
D O I：
10.7776/ASK.2015.34.3.240
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
In this paper, speech enhancement using nonnegative matrix factorization with temporal continuity has been addressed. Speech and noise signals are modeled as Possion distributions, and basis vectors and gain vectors of NMF are modeled as Gamma distributions. Temporal continuity of the gain vector is known to be critical to the quality of enhanced speech signals. In this paper, temporal continiuty is implemented by adopting Gamma-Markov chain priors for noise gain vectors during the separation phase. Simulation results show that the Gamma-Markov chain models temporal continuity of noise signals and track changes in noise effectively.
引用
收藏
页码：240 / 246
页数：7
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