Download Blind Speech Separation (Signals and Communication by Shoji Makino, Te-Won Lee, Hiroshi Sawada PDF

By Shoji Makino, Te-Won Lee, Hiroshi Sawada

This can be the world’s first edited e-book on autonomous part research (ICA)-based blind resource separation (BSS) of convolutive combos of speech. This publication brings jointly a small variety of top researchers to supply tutorial-like and in-depth therapy on significant ICA-based BSS issues, with the target of turning into the definitive resource for present, complete, authoritative, and but obtainable remedy.

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Additional info for Blind Speech Separation (Signals and Communication Technology)

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Murata, S. Ikeda, and A. Ziehe, “An approach to blind source separation based on temporal structure of speech signals,” Neurocomputing, vol. 41, pp. 1–24, Oct. 2001. 37. L. Parra and C. Spence, “Convolutive blind separation of non-stationary sources,” IEEE Trans. Speech Audio Processing, vol. 8, no. 3, pp. 320–327, May 2000. 38. S. Haykin, Adaptive Filter Theory, 4th ed. Prentice Hall, 2001. 39. P. Smaragdis, “Blind separation of convolved mixtures in the frequency domain,” Neurocomputing, vol.

Shown in Fig. 11 are the SIR improvements obtained by the various algorithms for the various processing strategies on the two-source mixture data. We plot the output SIR computed between the outputs of the separation filters and the original speech sources versus the input SIR computed between the outputs of the sensors and the original speech sources. From Fig. 11, Comparison of CBSS Algorithms in Power Imbalance − 2 source case 20 Stronger talker Weaker talker Output SIR [dB] 15 10 5 STFICA STFICA-Symm PARRA GEOBSS TRUNC-NG SNGTD SNGFD 0 −5 −15 −10 −5 0 Input SIR [dB] Fig.

The algorithm enjoys a number of useful properties, including fast convergence, guaranteed global convergence for certain mixing conditions and contrasts, and robust behavior when noise is present. More forms of contrast function can be obtained by different choices of Φ[yi ]. Spatio-temporal extensions. Spatio-temporal extensions of contrastbased methods involve additional constraints beyond spatial whitening and coefficient orthogonality. 57) 20 Scott C. Douglas and Malay Gupta • Under the above signal prewhitening constraints, the separation system must be constrained to be a paraunitary filter bank [30] to ensure component uniqueness.

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