An hmm-based cepstral-domain speech enhancement system
نویسندگان
چکیده
This paper describes a method of enhancing speech corrupted by additive uncorrelated noise. The approach adopted is to use cepstral-domain hidden Markov models to determine statistics of the clean speech and noise processes. A compensated model of speech corrupted by noise is generated using parallel model combination. MMSE and linear non-homogeneous estimators of the clean speech signal are derived. The enhancement system gives natural sounding speech without the artifacts introduced by systems such as spectral subtraction. HMM recognition tests performed on the enhanced speech using the NOISEX-92 database show a signiicant reduction in error rate.
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