Speech enhancement using arch model

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.

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