Noisy speech recognition using cepstral-time features and spectral-time filters

This paper explores the advantages of using cepstral-time feature matrices, and spectral-time filters, for noisy speech recognition within a hidden Markov model framework. The use of cepstral-time features with spectral subtraction and state-based time-varying Wiener filters is investigated. Experimental results indicate that cepstral-time features, and spectral-time noise processing, provide an effective framework for robust speech recognition in noisy environments.<
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