基于最小方差反卷积的新一代助听器语音增强系统

Huiqin Gao, M. Savic, Jeffrey Scott Sorensen
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引用次数: 0

摘要

描述了一种在多扬声器噪声环境中增强特定说话者语音的新方法。该方法的许多潜在应用是可能的,包括在新一代助听器中的实施。该系统基于最小方差反卷积(MVD)算法。使用TIMIT语音数据库对该方法进行了测试。首先将两个说话者的话语组合成一个多说话者环境,然后使用MVD算法进行分离。分离和增强的语音的可理解性很高。同样,原始语音的频谱与两个说话者的分离和增强语音的频谱非常相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Minimum variance deconvolution based-speech enhancement system for a new generation of hearing aids
Describes a novel method for the enhancement of speech of a particular speaker in a noisy multispeaker environment. Many potential applications of the method are possible including the implementation in a new generation of hearing aids. The system is based on the minimum variance deconvolution (MVD) algorithm. The method was tested using the TIMIT speech database. The utterances of two speakers were first combined to create a multispeaker environment, and then separated using the MVD algorithm. The intelligibility of the separated and enhanced speech was high. Likewise the frequency spectra of the original speech were very similar to the spectra of the separated and enhanced speech for each of the two speakers.<>
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