Proceedings of 1998 International Conference on Neural Information Processing (ICONIP'98), pp. 737–742

Authors:

  • Shiro Ikeda
  • Noboru Murata

Keywords:

  • sound separation
  • ICA
  • signal processing

Abstract:

In this article, we propose an Blind Source Separation algorithm for convolutive mixture of signals. We propose a method of separating signals in the time-frequency domain. We apply the decorrelation method proposed by Molgedey and Schuster on spectrogram and reconstruct separated signals focusing on the temporal structure of the signals. We show some results of experiments with both artificially controlled data and speech data recorded in the real environment.