论文标题
构音障碍，语音和神经型言语之间的自动和感知歧视
Automatic and perceptual discrimination between dysarthria, apraxia of speech, and neurotypical speech
论文作者
论文摘要
运动语音障碍（MSD）的自动技术通常是旨在区分构音障碍和神经型言语的两类技术，或者是构音障碍和语音中的语言（AOS）（AOS）。此外，尽管提出了这种技术来支持临床医生的感知评估，但从未比较自动和感知分类的精度。在本文中，我们研究了三级自动技术和一组手工制作的特征，以歧视构音障碍，AOS和神经型语音。提出了一种分层方法，而不是遵循常用的单一或单一式方法进行多级分类的方法。此外，还进行了一项感知研究，要求言语和语言病理学家聆听构想障碍，AOS和神经型言语的录音，并决定录音所属的阶级。在相同的记录上评估了所提出的自动技术，并比较自动和感知分类的性能。提出的结果表明，层次分类方法比基线单相位和一式式方法的方法具有更高的分类精度。此外，提出的结果表明，自动方法比对语音和语言病理学家的感知评估产生的分类精度更高，这证明了将自动工具整合到临床实践中的潜在优势。
Automatic techniques in the context of motor speech disorders (MSDs) are typically two-class techniques aiming to discriminate between dysarthria and neurotypical speech or between dysarthria and apraxia of speech (AoS). Further, although such techniques are proposed to support the perceptual assessment of clinicians, the automatic and perceptual classification accuracy has never been compared. In this paper, we investigate a three-class automatic technique and a set of handcrafted features for the discrimination of dysarthria, AoS and neurotypical speech. Instead of following the commonly used One-versus-One or One-versus-Rest approaches for multi-class classification, a hierarchical approach is proposed. Further, a perceptual study is conducted where speech and language pathologists are asked to listen to recordings of dysarthria, AoS, and neurotypical speech and decide which class the recordings belong to. The proposed automatic technique is evaluated on the same recordings and the automatic and perceptual classification performance are compared. The presented results show that the hierarchical classification approach yields a higher classification accuracy than baseline One-versus-One and One-versus-Rest approaches. Further, the presented results show that the automatic approach yields a higher classification accuracy than the perceptual assessment of speech and language pathologists, demonstrating the potential advantages of integrating automatic tools in clinical practice.
