Robust front-end for speech recognition by human and machine in noisy reverberant environments: The effect of phase information

摘要

This paper proposes a robust front-end for speech applications based on restoration scheme of instantaneous amplitude and phase. Typical applications such as hearing aids and automatic speech recognition systems still have challenging issues with regard to robustness against noise and reverberation. The proposed front-end employed a combination of our previously proposed method for restoring instantaneous amplitude and phase on a Gammatone filterbank and cepstral mean normalization (CMN). The first method can remove late reverberated and additive noise components from the observed speech, while the second method can remove the early reflection. In this paper, we comparatively evaluated the proposed method with other typical methods as robust front-end for speech recognition by human and machine in noisy reverberant environments. Modified Rhyme tests and word recognition tests were carried out as speech recognition by human and machine. The results of both evaluations revealed that the proposed front-end could effectively improve correctness of speech intelligibility and word recognition rate in noisy reverberant environments. In addition, effect of phase information was found to greatly improve the quality and intelligibility of speech.