Beamspace-Domain Multichannel Nonnegative Matrix Factorization for Audio Source Separation

被引:15
|
作者
Lee, Seokjin [1 ]
Park, Sang Ha [1 ]
Sung, Koeng-Mo [1 ]
机构
[1] Seoul Natl Univ, INMC, Seoul 151472, South Korea
关键词
Acoustic signal processing; blind source separation; multichannel audio; nonnegative matrix factorization (NMF); MIXTURES;
D O I
10.1109/LSP.2011.2173192
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this letter, we develop a multichannel blind source separation algorithm based on a beamspace transform and the multichannel nonnegative matrix factorization (NMF) method. The conventional multichannel NMF algorithm performs well with multichannel mixing data, but there is still room for enhancement in multichannel real-world recording data. In this letter, we consider a beamspace-time-frequency domain data model for multichannel NMF method, and enhance the conventional method using a beamspace transform. Our decomposition algorithm is applied to 2-channel and 4-channel unsupervised audio source separation, using a dataset from the international Signal Separation Evaluation Campaign 2010 (SiSEC 2010). Our algorithm shows a better performance than the conventional NMF method in an evaluation results.
引用
收藏
页码:43 / 46
页数:4
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