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Beamspace-Domain Multichannel Nonnegative Matrix Factorization for Audio Source Separation

delete2012-01-01
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PRE
AI
S
Seokjin Lee *
S
Sang Ha Park
DOI:10.1109/LSP.2011.2173192delete
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摘要

摘要

En 中文
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.
Keyword:
Acoustic signal processing
blind source separation
multichannel audio
nonnegative matrix factorization (NMF)
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期刊

IEEE Signal Processing Magazine 封面图
IEEE Signal Processing Magazine
IF:
9.6
论文数:
1.1W
被引数:
1.7W

机构

S
seoul national university (snu)
学者数:
7.2W
论文数: 6.6W
被引数: 86
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