An identification of speaker-dependence in reverberant-robust speech recognition

Abstract

In recent years, a hands-free speech device has been developed with improving speech-recognition techniques. There is, however, a problem that the reverberant speech degrades the recognition performance in the field of distant-talking speech recognition. It is possibly addressed by taking preventive measures against the degradation of recognition performance with the reverberant criteria to estimate the recognition performance. We have already proposed the method to estimate recognition performance with ISO3382 acoustic parameter based on an impulse response. In this method, the recognition performance was estimated without speech features. Identification of the speaker with robust or weak features against reverberation makes it possible to adapt acoustic model for each speaker toward improving the recognition performance. In this research, we designed the speaker-dependence criteria in reverberant speech recognition. We first investigated existence of the speaker with robust or weak features against reverberation in various reverberant environments. After that, we compared clean and reverberant speech data in terms of speech features such as MFCC, delta MFCC, delta power, and utterance speed to evaluate the effects of reverberation on speech recognition. An experimental result showed the utterance speed was one of the effective candidates for the identification of speaker-dependence in reverberant-robust speech recognition.