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Abstract : |
Mismatch in training and testing conditions reduces considerably the performance of a speaker-independent HMM-based continuous speech recognizer. Compensation of this mismatch can avoid the complex and time-consuming retraining of the recognizer. This paper describes an acquisition system based on a four omnidirectional microphone array that was employed to reproduce a "beamformed " version of the original acoustic messages acquired in a noisy and reverberant environment, with a talker-microphone distance of one meter. In this preliminary activity, some simple noise compensation techniques (i.e. a Mean Spectrum based Enhancement and a Cepstrum Mean Subtraction) were incorporated in this preprocessing stage to obtain an enhanced version of the given utterance. Feeding a clean-condition trained continuous speech recognizer with enhanced signals led to a significant improvement of performance, if compared to the use of unprocessed single-microphone signals as input., |
