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Speech Enhancement using Adaptive Mean Median Deviation and EMD Technique

机译:使用自适应平均中值偏差和EMD技术的语音增强

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During the acquisition of the speech signal by the non-contact Speech Sensor (SS), the signal is degraded by severe colored noises which are non-linear and non-uniform in nature. Therefore, in this study, a new approach for advancing the speech enhancement technique is proposed to suppress these noises from the acquired speech signal. This technique is based on the adaptive thresholding, which uses Mean Median Deviation (MMD) method to determine adaptive threshold points, and Empirical Mode Decomposition (EMD) method. This algorithm has been validated by simulation data, and results of the proposed algorithm have been compared with other existing enhancement algorithms. Spectrograms and Signal to Noise Ratio (SNR) comparison are used to analyze the quality of the enhanced speech signal. From the results, we demonstrate that the proposed algorithm offers better speech enhancement than previously existing speech enhancement techniques.
机译:在非接触式语音传感器(SS)采集语音信号的过程中,信号会由于严重的彩色噪声而降级,这些噪声本质上是非线性且不均匀的。因此,在这项研究中,提出了一种用于改进语音增强技术的新方法,以抑制所获取的语音信号中的这些噪声。该技术基于自适应阈值处理,该方法使用均值中位数偏差(MMD)方法确定自适应阈值点,并使用经验模式分解(EMD)方法。仿真算法验证了该算法的有效性,并将该算法的结果与其他现有的增强算法进行了比较。频谱图和信噪比(SNR)比较用于分析增强语音信号的质量。从结果中,我们证明了所提出的算法比以前现有的语音增强技术提供了更好的语音增强。

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