scholarly journals Non-Negative Matrix Factorization with Sparsity Learning for Single Channel Audio Source Separation

10.5772/48068 ◽  
2012 ◽  
Author(s):  
Bin Gao ◽  
W.L. Woo
Keyword(s):  
Matrix Factorization ◽  
Single Channel ◽  
Source Separation ◽  
Audio Source Separation ◽  
Non Negative Matrix Factorization

Prior structures for non‐negative matrix factorization based audio source separation.

2008 ◽  
Vol 124 (4) ◽  
pp. 2571-2571
Author(s):  
Tuomas Virtanen ◽  
Ali Taylan Cemgil
Keyword(s):  
Matrix Factorization ◽  
Source Separation ◽  
Audio Source Separation ◽  
Non Negative Matrix Factorization

scholarly journals Sampled and discretized of short-time Fourier transform and non-negative matrix factorization: the single-channel source separation case

2020 ◽  
Vol 9 (1) ◽  
pp. 41-48
Author(s):  
Jans Hendry ◽  
Isnan Nur Rifai ◽  
Yoga Mileniandi
Keyword(s):  
Fourier Transform ◽  
Matrix Factorization ◽  
Single Channel ◽  
Source Separation ◽  
Short Time Fourier Transform ◽  
Time Frequency ◽  
Frequency Representation ◽  
Short Time ◽  
Better Than ◽  
Non Negative Matrix Factorization

The Short-time Fourier transform (STFT) is a popular time-frequency representation in many source separation problems. In this work, the sampled and discretized version of Discrete Gabor Transform (DGT) is proposed to replace STFT within the single-channel source separation problem of the Non-negative Matrix Factorization (NMF) framework. The result shows that NMF-DGT is better than NMF-STFT according to Signal-to-Interference Ratio (SIR), Signal-to-Artifact Ratio (SAR), and Signal-to-Distortion Ratio (SDR). In the supervised scheme, NMF-DGT has a SIR of 18.60 dB compared to 16.24 dB in NMF-STFT, SAR of 13.77 dB to 13.69 dB, and SDR of 12.45 dB to 11.16 dB. In the unsupervised scheme, NMF-DGT has a SIR of 0.40 dB compared to 0.27 dB by NMF-STFT, SAR of -10.21 dB to -10.36 dB, and SDR of -15.01 dB to -15.23 dB.

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