使用多级维纳滤波器的语音增强

M. Tinston, Y. Ephraim
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引用次数: 6

摘要

本文提出了一种子空间语音增强方法,用于估计被加性不相关噪声退化的信号。这个问题有许多应用,如助听器和嘈杂环境中的自动语音识别。该方法采用多级维纳滤波器(MWF)。该滤波器由与该问题的维纳滤波器相关联的Krylov子空间构造而成。介绍了该方法的原理和性能。与全维纳滤波和信号子空间方法相比,该方法提供的信号质量更高,这一点从非正式主观听力测试、常用的PESQ客观测试和语音识别性能的提高中可以看出。在非正式听力测试中,听众更喜欢MWF增强方法而不是其他增强方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speech enhancement using the multistage Wiener filter
In this paper we develop a subspace speech enhancement approach for estimating a signal which has been degraded by additive uncorrelated noise. This problem has numerous applications such as in hearing aids and automatic speech recognition in noisy environments. The proposed approach utilizes the multistage Wiener filter (MWF). This filter is constructed from a Krylov subspace associated with the Wiener filter for this problem. The principles and performance of this approach are described. The approach provides signals with higher quality compared to the fullWiener filter and the signal subspace method as evident from informal subjective listening tests, the commonly used PESQ objective test and improved speech recognition performance. In informal listening tests the listeners preferred the MWF enhancement over the other enhancement methods.
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