SPEECH RECOGNITION IN NOISY ENVIRONMENTS - A SURVEY

The performance levels of most current speech recognizers degrade sign ificantly when environmental noise occurs during use. Such performance degradation is mainly caused by mismatches in training and operating environments. During recent years much effort has been directed to red ucing this mismatch. This paper surveys research results in the area o f digital techniques for single microphone noisy speech recognition cl assified in three categories: noise resistant features and similarity measurement, speech enhancement, and speech model compensation for noi se. The survey indicates that the essential points in noisy speech rec ognition consist of incorporating time and frequency correlations, giv ing more importance to high SNR portions of speech in decision making, exploiting task-specific a priori knowledge both of speech and of noi se, using class-dependent processing, and including auditory models in speech processing.