Robust noise reduction for speech and audio signals

  • Authors:

  • S. J. Godsill;P. J. W. Rayner

  • Affiliations:

  • Dept. of Eng., Cambridge Univ., UK;-

  • Venue:
  • ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
  • Year:
  • 1996

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Abstract

Statistical model-based methods are presented for the reconstruction of autocorrelated signals in impulsive plus continuous noise environments. Signals are modelled as autoregressive and noise sources as discrete and continuous mixtures of Gaussians, allowing for robustness in highly impulsive and non-Gaussian environments. Markov Chain Monte Carlo methods are used for reconstruction of the corrupted waveforms within a Bayesian probabilistic framework and results are presented for contaminated voice and audio signals.