In most current approaches of speech processing, information is extracted from the magnitude spectrum. However recent perceptual studies have underlined the importance of the phase component. The goal of this paper is to investigate the potential of using phase-based features for automatically detecting voice disorders. It is shown that group delay functions are appropriate for characterizing irregularities in the phonation. Besides the respect of the mixed-phase model of speech is discussed. The proposed phase-based features are evaluated and compared to other parameters derived from the magnitude spectrum. Both streams are shown to be interestingly complementary. Furthermore phase-based features turn out to convey a great amount of relevant information, leading to high discrimination performance.

中文翻译：

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基于相位的语音病理检测信息

在大多数当前的语音处理方法中，信息是从幅度谱中提取的。然而，最近的感知研究强调了相位分量的重要性。本文的目的是研究使用基于相位的特征自动检测语音障碍的潜力。结果表明，群延迟函数适用于表征发声中的不规则性。此外还讨论了语音的混合相位模型方面。所提出的基于相位的特征被评估并与从幅度谱导出的其他参数进行比较。两个流都显示出有趣的互补性。此外，基于相位的特征可以传达大量相关信息，从而实现高鉴别性能。