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A framework for predicting speech quality using detectability of multiple distortions

机译:利用多重失真的可检测性预测语音质量的框架

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摘要

This paper proposes a framework for predicting overall speech quality using a multi-dimensional analysis of individual distortions. The algorithm makes use of a physiologically motivated hydro-mechanical Cochlear Model to convert the speech signal into a domain that is more representative of what is perceived. Salient features are extracted and compared between the original and degraded representations to analyze the detectability of individual distortions. These are subsequently combined to predict overall quality.
机译:本文提出了使用单个失真的多维分析来预测总体语音质量的框架。该算法利用生理动机的水力机械Cochlear模型将语音信号转换为更能代表所感知内容的域。提取显着特征并在原始表示和降级表示之间进行比较,以分析单个失真的可检测性。随后将它们组合以预测整体质量。

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