HIDDEN MARKOV MODEL STATE-BASED NOISE CANCELLATION
V. L. Beattie and S. J. Young
This report summarizes the work done at Cambridge University Engineering Department on developing noise-robust algorithms within a Hidden Markov Model recognition system. The aim of this research has been to develop noise-robust algorithms for use within the HMM recognition framework, as opposed to noise cancellation or compensation at the preprocessing level. Such algorithms can take advantage of the clean speech model presented by the HMMs themselves. This research formed part of ESPRIT Project p.2101, ``Adverse-Environment Recognition of Speech'' (ARS).
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