Objective evaluation of speech enhancement using compressive sensing algorithm

Amart Sulong, T. Gunawan, Othman 0. Khalifa, J. Chebil
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Abstract

Most of the accurate method for the speech enhancement design mainly focuses on quality and intelligibility to produce high performance level by using compression techniques. A novel speech enhancement algorithm using compressive sensing (CS) is different paradigm from compression technique with low-dimensional geometry for transmission or storage. The CS algorithm, can directly acquire compressed data signals and replace samples by more general measurements of the uniform rate digitization with signal sparsity model. Perceptual evaluation of speech quality (PESQ) is an objective evaluation of speech enhancement algorithm used to measure the enhanced speech quality. All provable good measurement, with random matrics in CS algorithm, can enhance speech signal. Objective evaluation on various dB SNR shows that the proposed algorithm exhibits better noise reduction ability over conventional approaches without obvious degradation of the speech signal quality.
压缩感知语音增强算法的客观评价
大多数精确的语音增强设计方法主要集中在质量和可理解性上,利用压缩技术产生高性能的语音增强。一种基于压缩感知(CS)的语音增强算法是一种不同于基于低维几何结构的传输或存储压缩技术的新范式。CS算法,可以直接获取压缩后的数据信号,用信号稀疏化模型下更一般的均匀率数字化测量代替采样。语音质量感知评价(PESQ)是一种对语音增强算法进行客观评价的方法,用来衡量增强后的语音质量。所有可证明的良好测量,在CS算法中使用随机矩阵,可以增强语音信号。对各种dB信噪比的客观评价表明,该算法比传统方法具有更好的降噪能力,且语音信号质量没有明显下降。
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