Real-time online singing voice separation from monaural recordings using robust low-rank modeling

Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012

Volumn , Issue , 2012, Pages 67-72

  Sprechmann, Pablo ^a   Bronstein, Alex ^b   Sapiro, Guillermo ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

^b TEL AVIV UNIVERSITY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMANTS; AUDIO APPLICATIONS; DATA SETS; FEED-FORWARD; LOW LATENCY; NONNEGATIVE MATRIX FACTORIZATION; OPTIMIZATION METHOD; ORDERS OF MAGNITUDE; PERFORMANCE DEGRADATION; PROCESSING APPLICATIONS; REPETITIVE STRUCTURE; ROBUST PRINCIPAL COMPONENT ANALYSIS; STATE-OF-THE-ART PERFORMANCE; VOICE SEPARATION;

PRINCIPAL COMPONENT ANALYSIS;

INFORMATION RETRIEVAL;

EID: 84873423755     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. F. Bach, R. Jenatton, J. Mairal, and G. Obozinski. Convex optimization with sparsity-inducing norms. In Optimization for Machine Learning. MIT Press, 2011.
2. A. Beck and M. Teboulle. A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Img. Sci., 2:183-202, March 2009.
3. E. Candès, X. Li, Y. Ma, and J. Wright. Robust principal component analysis? Journal of the ACM, 58(3), May 2011.
4. J.-L. Durrieu, B. David, and G. Richard. A musically motivated mid-level representation for pitch estimation and musical audio source separation. J. Sel. Topics Signal Processing, 5(6):1180-1191, 2011.
5. I. Goodfellow, Q. Le, A. Saxe, H. Lee, and A. Y. Ng. Measuring invariances in deep networks. In NIPS, pages 646-654. 2009.
6. K. Gregor and Y. LeCun. Learning fast approximations of sparse coding. In ICML, pages 399-406, 2010.
7. M. Henaff, K. Jarrett, K. Kavukcuoglu, and Y. LeCun. Unsu-pervised learning of sparse features for scalable audio classification. In ISMIR, 2011.
8. C.L. Hsu and J.S.R. Jang. On the improvement of singing voice separation for monaural recordings using the MIR-1K dataset. IEEE Trans. on Audio, Speech, and Lang. Proc., 18(2):310-319, 2010.
9. P.-S. Huang, S. D. Chen, P. Smaragdis, and M. Hasegawa-Johnson. Singing-voice separation from monaural recordings using robust principal component analysis. In ICASSP, 2012.
10. K. Kavukcuoglu, M.A. Ranzato, and Y. LeCun. Fast inference in sparse coding algorithms with applications to object recognition. arXiv:1010.3467, 2010.
11. Y. Li and D. L. Wang. Separation of singing voice from music accompaniment for monaural recordings. IEEE Trans. on Audio, Speech & Lang. Proc., 15(4):1475-1487, 2007.
12. Z. Lin, M. Chen, and Y. Ma. The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. Arxiv preprint arXiv:1009.5055, 2010.
13. A. Liutkus, Z. Rai, R. Badeau, B. Pardo, and G. Richard. Adaptive filtering for music/voice separation exploiting the repeating musical structure. In ICASSP, 2012.
14. G. Mateos and G. B. Giannakis. Robust PCA as bilinear decomposition with outlier-sparsity regularization. arXiv.org:1111.1788, 2011.
15. A. Ozerov, P. Philippe, F. Bimbot, and R. Gribonval. Adaptation of bayesian models for single-channel source separation and its application to voice/music separation in popular songs. IEEE Trans. on Audio, Speech & Lang. Proc., 15(5):1564-1578, 2007.
16. M. A. Ranzato, F. J. Huang, Y.-L. Boureau, and Y. LeCun. Un-supervised learning of invariant feature hierarchies with applications to object recognition. In CVPR, 2007.
17. B. Recht, M. Fazel, and P. A. Parrilo. Guaranteed minimumrank solutions of linear matrix equations via nuclear norm minimization. SIAM Rev., 52(3):471-501, 2010.
18. B. Recht and C. Ré. Parallel stochastic gradient algorithms for large-scale matrix completion. 2011.
19. S. Vembu and S. Baumann. Separation of vocals from polyphonic audio recordings. In ISMIR, pages 337-344, 2005.
20. E. Vincent, R. Gribonval, and C. Févotte. Performance measurement in blind audio source separation. IEEE Trans. on Audio, Speech, and Lang. Proc., 14(4):1462-1469, 2006.
21. H. Xu, C. Caramanis, and S. Sanghavi. Robust PCA via outlier pursuit. In NIPS, pages 2496-2504. 2010.
22. L. Zhang, Z. Chen, M. Zheng, and X. He. Robust non-negative matrix factorization. Frontiers of Electrical and Electronic Engineering in China, 6:192-200, 2011.