A Study on Restoration of Bone-Conducted Speech with MTF-Based and LP-Based Models

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  • Study on Restoration of Bone Conducted Speech with MTF Based and LP Based Models

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Bone-conducted speech in an extremely noisy environment seems to be more advantageous than normal noisy speech (i.e., noisy air-conducted speech) because of its stability against surrounding noise. The sound quality of bone-conducted speech, however, is very low and restoring bone-conducted speech is a challenging new topic in the speech signal-processing field. We describe two types of models for restoration: one based on the modulation transfer function (MTF) and the other based on linear prediction (LP). The MTF-based model is expected to yield a restored signal with higher intelligibility while the LP-based model is expected to yield one that is not only more intelligible to human hearing systems but also enables automatic speech recognition (ASR) systems to achieve better performance. To evaluate the ability of these models to improve voice-quality, we compared them with the other previous two models using one subjective and three objective measurements. The mean opinion score (MOS) and log-spectrum distortion (LSD) were used to evaluate the improvements in intelligibility, which is useful for human hearing systems. The distances based on LP coefficients and mel-frequency cepstral coefficients (MFCCs) were used to evaluate improvements in cepstral distances which are useful for ASR systems. The results proved that both the MTF-based and LP-based models are better than the other previous models for improving intelligibility. They particularly proved that LP-based models produces the best results for both human hearing and ASR systems.

identifier:1342-6230

identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/4015

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