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Speech enhancement using arch model

机译:使用弓形模型进行语音增强

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摘要

In this paper, we investigate the use of the autoregressive conditional heteroscedasticity (ARCH) model as a replacement to the decision-directed method in the log-spectral amplitude estimator for speech enhancement. We employ three sound quality measures: speech distortion, noise reduction and musical noise, and explain the effect the ARCH model parameters have on these measures. We demonstrate and compare the use of the decision-directed and ARCH estimators and show that the ARCH model achieves better results than the decision-directed for some of these measures, while compromising between the speech distortion and noise reduction.
机译:在本文中,我们研究了使用自回归条件异方差性(ARCH)模型替代对数频谱幅度估计器中用于语音增强的决策导向方法。我们采用三种声音质量度量:语音失真,降噪和音乐噪声,并说明ARCH模型参数对这些度量的影响。我们演示并比较了决策导向和ARCH估计器的使用,并表明ARCH模型比其中某些方法的决策导向取得了更好的结果,同时在语音失真和降噪之间做出了妥协。

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