In this paper, the performance of compressive sensing (CS)-based technique for speech enhancement has been studied and results analyzed with recovery algorithms as a comparison of their performances. This is done for several recovery algorithms such as matching pursuit, orthogonal matching pursuit, stage-wise orthogonal matching pursuit, compressive sampling matching pursuit and generalized orthogonal matching pursuit. Performances of all these greedy algorithms were compared for speech enhancement. The evaluation of results has been carried out using objective measures (perceptual evaluation of speech quality, log-likelihood ratio, weighted spectral slope distance and segmental signal-to-noise ratio), simulation time and composite objective measures (signal distortion CSIG, background intrusiveness CBAK and overall quality COVL). Results showed that the CS-based technique using generalized orthogonal matching pursuit algorithm yields better performance than the other recovery algorithms in terms of speech quality and distortion.

中文翻译：

---

语音增强系统贪心算法的性能比较评估

在本文中，研究了基于压缩感知 (CS) 的语音增强技术的性能，并使用恢复算法对结果进行了分析，以比较它们的性能。这是为几种恢复算法完成的，例如匹配追踪、正交匹配追踪、逐级正交匹配追踪、压缩采样匹配追踪和广义正交匹配追踪。比较所有这些贪心算法的性能以进行语音增强。使用客观测量（语音质量的感知评估、对数似然比、加权谱斜率距离和分段信噪比）、模拟时间和复合客观测量（信号失真C小号一世G, 背景侵入性C乙一种ķ和整体质量C○五大号). 结果表明，使用广义正交匹配追踪算法的基于CS的技术在语音质量和失真方面比其他恢复算法具有更好的性能。