Comparative evaluation of modulation-transfer-function-based blind restoration of sub-band power envelopes of speech as a front-end processor for automatic speech recognition systems

Abstract

To reduce speech degradation in reverberant environments, we previously proposed a modulation-transfer-function (MTF)-based method of speech dereverberation. By considering the temporal modulation properties of speech, and the exponential decay properties of the power envelope of the impulse response of room acoustics, we obtained the following MTF relation: the sub-band power envelope of reverberant speech that can be represented as a convolution between the sub-band power envelope of clean speech and the power envelope of the impulse response of room acoustics. On the basis of the MTF relation, inverse MTF filtering can be applied to restoring the power envelopes of reverberant speech. Therefore, the impulse response of the room acoustics in this restoration dose not need to be measured at any time since we model the power envelope of the impulse response as an exponential decay function. We have tested how effective this method is as a front-end for automatic speech recognition (ASR) systems in artificial and real reverberant environments. Reverberant speech signals were created by simply convoluting clean speech (AURORA-2J database) with the artificially produced or real impulse responses of room acoustics. A method based on the auditory power spectrum was used as a baseline for comparison. Compared with the baseline, the proposed method for artificial reverberant environments produced a 35.67% relative improvement in the error reduction rate (on average, for reverberation times from 0.2 to 2.0 s), and for real reverberant environments (43 reverberant impulse responses), it produced a 25.78% relative improvement in the error reduction rate. The results demonstrate that our new approach can improve the robustness of speech-recognition systems in reverberant environments, and it performs better than conventional methods.