  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.
