Stereophonic speech recognition in noise using compensated hidden Markov models
A novel procedure is presented for noise compensation in hidden Markov model speech recognisers. The procedure uses two microphone signals and, unlike previous approaches, does not require the noise spectrum to be stationary even in the short term. Results are presented showing that the performance of the compensated system equals or exceeds that obtained using matched training.