Classifications of vocalic segments from articulatory kinematics: healthy controls and speakers with dysarthria.

Purpose: In this study, the authors classified vocalic segments produced by control speakers (C) and speakers with dysarthria due to amyotrophic lateral sclerosis (ALS) or Parkinson's disease (PD); classification was based on movement measures. The researchers asked the following questions: (a) Can vowels be classified on the basis of selected measures of articulatory motions? and (b) Can classification models that are constructed from control productions classify vowels produced by speakers with dysarthria that is related to ALS and PD?

Method: Nineteen C, 7 PD, and 8 ALS speakers participated in this study. The severity of dysarthria varied across individuals and between the 2 disorder groups. The stimuli were 6 vowels produced in 10 words embedded into sentences read at a comfortable reading rate. Movement data were collected using the x-ray microbeam. Movement measures included distances traveled, durations, and average speeds of vowel-related movement strokes. Vowels and words were classified by linear discriminant analysis with measures of articulatory motion as input variables.

Results: The study showed that vocalic segments could be classified using articulatory movement characteristics with up to 80% accuracy. The classification accuracy of the movement-based models depended largely on the number of articulators involved and, to a lesser extent, on the movement measure (e.g., distance, duration, speed). Classification of PD vowels was similar to that of the C group, suggesting a simple scaling of gestures as an explanation of the movement deficit in this disease. Classification performance for ALS vowels appeared to be different from that of C and PD productions.

Conclusion: Classification of vowels was possible on the basis of their articulatory motions. ALS vowels appeared categorically different from those of C and PD speakers.