Speech separation by kurtosis maximization

  title={Speech separation by kurtosis maximization},
  author={James P. LeBlanc and Phillip L. De Leon},
We present a computationally efficient method of separating mixed speech signals. The method uses a recursive adaptive gradient descent technique with the cost function designed to maximize the kurtosis of the output (separated) signals. The choice of kurtosis maximization as an objective function (which acts as a measure of separation) is supported by experiments with a number of speech signals as well as spherically invariant random processes (SIRP’s) which are regarded as excellent… CONTINUE READING
Highly Cited
This paper has 47 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 34 extracted citations


Publications referenced by this paper.
Showing 1-10 of 17 references

An experimental study of speechwave probability distributions

  • Davenport, B W.
  • Journal of the Acoustical Society of America,
  • 1952
Highly Influential
5 Excerpts

A New Approach to Multipath Correction of Constant Modulus Signals

  • J. R. Treichler, M. G. Agee
  • IEEE Trans. on Acoustics, Speech, and Signal…
  • 1983
Highly Influential
7 Excerpts

New self-adaptive algorithm for source separation based on contrast functions

  • E. Moreau, O. Macchi
  • Proc. IEEE Signal Processing Workshop on Higher…
  • 1993
1 Excerpt

Similar Papers

Loading similar papers…