Abstract for logan_sst96

Proc. 6th Australian International Conference on Speech Science and Technology, 1996.


B. T. Logan and A. J. Robinson

Dec 1996

This paper describes a new algorithm to enhance and recognise noisy speech when only the noisy signal is available. The system uses autoregressive hidden Markov models (HMMs) to model the clean speech and noise and combines these to form a model for the noisy speech. The combined model is used to determine the likelihood of each observation being just noise. These likelihoods are used to weight each observation to form a new estimate of the noise and the process is repeated. Enhancement is performed using Wiener filters formed from the clean speech and noise models. Results are presented for additive stationary Gaussian and coloured noise.

(ftp:) logan_sst96.ps.Z (http:) logan_sst96.ps.Z
PDF (automatically generated from original PostScript document - may be badly aliased on screen):
  (ftp:) logan_sst96.pdf | (http:) logan_sst96.pdf

If you have difficulty viewing files that end '.gz', which are gzip compressed, then you may be able to find tools to uncompress them at the gzip web site.

If you have difficulty viewing files that are in PostScript, (ending '.ps' or '.ps.gz'), then you may be able to find tools to view them at the gsview web site.

We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.