Abstract
TIFCORR is a Blind Signal Separation technique that is well suited to separating audio signals, requiring each signal to be sparse in only a local time-frequency region of their representation [1]. TIFCORR can suffer from inconsistencies in mixing system estimation, thus we present a modified algorithm incorporating k-means clustering [2] to improve estimation robustness. To improve the data efficiency ofTIFCORR, we also include an adaptive weighting function for mixing column estimates. These modifications transform our algorithm into a block adaptive algorithm with the ability to track time-varying mixtures.
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References
Deville, Y.: Temporal and time frequency correlation based blind source separation methods. In: Proc.4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), pp. 1059–1064 (2003)
Gersho, A., Gray, R.: Vector Quantization and Signal Compression. Kluwer Academic Publishers, Dordrecht (1992)
Hyvarinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley & Sons, Chichester (2001)
Abrard, F., Deville, Y., White, P.: From blind source separation to blind source cancellation in the undetermined case: A new approach based on time-frequency analysis. In: Proc.3rd International Conference on Independent Component Analysis and Blind Source Separation (ICA 2001), pp. 734–739 (2001)
Choi, C.: Real time binaural blind source separation. In: Proc.4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), pp. 567–572 (2003)
Bofill, P., Zibulevsky, M.: Undetermined blind source separation using sparse representations. Signal Processing 81, 2353–2362 (2001)
Balan, R., Rosca, J., Rickard, S.: Scalable non-square blind source separation in the presence of noise. In: Proc.IEEE International Conference on Acoustics, Speech and Signal Signal Processing (ICASSP 2003), vol. 5, pp. 293–296 (2003)
Jourjine, A., Rickard, S., Yilmaz, O.: Blind separation of disjoint orthogonal signals: Demixing n sources from 2 mixtures. In: Proc.IEEE Conference on Acoustics, Speech, and Signal Processing (ICASSP2000), vol. 5, pp. 2985–2988 (2000)
Rickard, S., Yilmaz, O.: On the w-disjoint orthogonality of speech. In: Proc.IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2002), vol. 1, pp. 529–532 (2002)
Smith, D., Lukasiak, J., Burnett, I.: A block-adaptive audio separation technique based upon time-frequency information. In: Submitted to EUSIPCO 2004 (2004)
Cichoki, A., Amari, S.: Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications. John Wiley & Sons, Chichester (2002)
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© 2004 Springer-Verlag Berlin Heidelberg
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Smith, D., Lukasiak, J., Burnett, I. (2004). Two Channel, Block Adaptive Audio Separation Using the Cross Correlation of Time Frequency Information. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_112
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DOI: https://doi.org/10.1007/978-3-540-30110-3_112
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