Blind Separation of Speech by Fixed-Point ICA with Source Adaptive Negentropy Approximation

@article{Prasad2005BlindSO,
  title={Blind Separation of Speech by Fixed-Point ICA with Source Adaptive Negentropy Approximation},
  author={Rajkishore Prasad and Hiroshi Saruwatari and Kiyohiro Shikano},
  journal={IEICE Transactions},
  year={2005},
  volume={88-A},
  pages={1683-1692}
}
This paper presents a study on the blind separation of a convoluted mixture of speech signals using Frequency Domain Independent Component Analysis (FDICA) algorithm based on the negentropy maximization of Time Frequency Series of Speech (TFSS). The comparative studies on the negentropy approximation of TFSS using generalized Higher Order Statistics (HOS) of different nonquadratic, nonlinear functions are presented. A new nonlinear function based on the statistical modeling of TFSS by… CONTINUE READING
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Probability distribution of time-series of speech spectral components

  • R. Prasad, H. Saruwatari, K. Shikano
  • IEICE Trans. Fundamentals, vol.E87-A, no.3, pp…
  • 2004
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