Enhancement of connected words in an extremely noisy environment

A speech enhancement algorithm that is based on a connected-word hidden Markov model (HMM) is developed. Speech is assumed to be highly degraded by statistically independent additive noise. The minimum mean square error estimator is derived for a connected-word HMM. Further, we derive an estimator based on a connected-word HMM with explicit state duration. Listening experiments performed with digit strings have shown an increase of intelligibility. The best results were achieved when subjects who listened to the enhanced speech were given the results of an automatic recognition system.