论文标题
语音病理检测的基于阶段的信息
Phase-based Information for Voice Pathology Detection
论文作者
论文摘要
在大多数目前的语音处理方法中，从大小频谱中提取信息。但是，最近的感知研究强调了相分量的重要性。本文的目的是研究使用基于阶段的特征自动检测语音障碍的潜力。结果表明，组延迟函数适合表征发音中的不规则性。除了讨论了言语混合相模型的尊重之外。评估了所提出的基于阶段的特征，并将其与来自幅度光谱得出的其他参数进行了比较。两种流都被证明是有趣的补充。此外，基于阶段的功能可以传达大量相关信息，从而导致高歧视性能。
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.
