Abstract
Although many speech enhancement (SE) algorithms have been proposed to promote speech perception in hearing-impaired patients, the conventional SE approaches that perform well under quiet and/or stationary noises fail under nonstationary noises and/or when the speaker is at a considerable distance. Therefore, the objective of this study is to overcome the limitations of the conventional speech enhancement approaches. This study proposes a speaker-closed deep learning-based SE method together with an optical microphone to acquire and enhance the speech of a target speaker. The objective evaluation scores achieved by the proposed method outperformed the baseline methods by a margin of 0.21-0.27 and 0.34-0.64 in speech quality (HASQI) and speech comprehension/intelligibility (HASPI), respectively, for seven typical hearing loss types. The results suggest that the proposed method can enhance speech perception by cutting off noise from speech signals and mitigating interference caused by distance. The results of this study show a potential way that can help improve the listening experience in enhancing speech quality and speech comprehension/intelligibility for hearing-impaired people.
Published Version
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