Single-channel speech separation using empirical mode decomposition and multi pitch information with estimation of number of speakers

Author:

Prasanna Kumar M. K.,Kumaraswamy R.

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Reference34 articles.

1. Bofill, P. (2008). Identifying single source data for mixing matrix estimation in instantaneous blind source separation. Proceedings of the ICANN, 5163, 759–767.

2. Boldt, J. B., & Ellis, D. P. W. (2009) A simple correlation based model of intelligibility for nonlinear speech enhancement and separation. Columbia university academic commons, http://hdl.handle.net/10022/AC:P:13660 .

3. Digital Speech Processing Course (2015). Time domain methods in speech processing. http://www.ece.ucsb.edu/Faculty/Rabiner/ece259/speech20course.html .

4. Douglas, S. C., Sawada, H., & Makino, S. (2005). Natural gradient Multichannel blind deconvolution and speech separation using causal FIR filters. IEEE Transactions on Speech Audio Processing, 13(1), 92–104.

5. Ellis, D. (2006). Model based scene analysis. In D. Wang & G. Brown (Eds.), Computational auditory scene analysis: Principles, algorithms and applications. New York: Wiley.

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