Godsill, SJ and Rayner, PJW (1996) Robust noise reduction for speech and audio signals. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2. pp. 625-628. ISSN 0736-7791Full text not available from this repository.
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.
|Divisions:||Div F > Signal Processing and Communications|
|Depositing User:||Unnamed user with email firstname.lastname@example.org|
|Date Deposited:||18 May 2016 19:10|
|Last Modified:||27 Aug 2016 23:32|