HMM adaptation and microphone array processing for distant speech recognition

Connected strings of seven digits from the TIDIGITS database were recorded in a reverberant office room for evaluation using microphone array processing and HMM, hidden Markov model, adaptation. A sixteen-channel linear microphone array records a distance speech database useful for further experimentation. The adaptation techniques of parallel model combination (PMC) and maximum likelihood linear regression (MLLR) are evaluated and compared. The effect of the number of adaptation utterances and number of vectors per class for the regression tree in order to optimize MLLR results are studied. Results show, compared to no adaptation, 40% word error reduction (improvement to 4.2%) for PMC and 60% word error reduction (improvement to 3.0%) for MLLR