This paper explores use of synergistically-integrated systems of microphone arrays and neural networks for robust speech recognition in variable acoustic environments, where the user must not be encumbered by microphone equipment. Existing speech recognizers work best for "high-quality close-talking speech." Performance of these recognizers is typically degraded by environmental interference and mismatch in training conditions and testing conditions. It is found that use of microphone arrays and neural network processors can elevate the recognition performance of existing speech recognizers in an adverse acoustic environment, thus avoiding the need to retrain the recognizer, a complex and tedious task. We also present results showing that a system of microphone arrays and neural networks can achieve a higher word recognition accuracy in an unmatched training/testing condition than that obtained with a retrained speech recognizer using array speech for both training and testing, i.e., a matched training/testing condition.

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Hands-free operation of speech processing equipment is sometimes desired so that the user is unencumbered by hand-held or bodyworn microphones. This paper explores the use of array microphones and neural networks (MANN) for robust speech/speaker recognition in a reverberant and noisy environment. Microphone arrays (MA) provide high-quality, hands-free sound capture at distances, and neural network (NN) processors compensate for environmental interference by transforming speech features of the array input to those of close-talking microphone input. The MANN system is evaluated using both computer-simulated degraded speech and real-room collected speech. It is found that the MANN system is capable of elevating recognition accuracies under adverse conditions, such as room reverberation, noise interference, and mismatch between the training and testing conditions, to levels comparable to those obtained with close-talking microphone input under a matched training and testing condition. 0819416010/94/$6.OO SPIE Vol. 2277 / 121 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/27/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

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