Abstract
Patients affected by Amyotrophic Lateral Sclerosis (ALS) show specific dysarthric clues in speech. These marks could be used to detect early symptoms and monitor the evolution of the disease in time. Classically articulation marks have been mainly based on static premises. Articulation Kinematics from acoustic correlates may help in producing measurements based on the dynamic behavior of speech. Specifically, distribution functions from the absolute kinematic velocity estimated by a simplified articulation model can be used in establishing distances based on Information Theory concepts between running speech segments from patients and controls. As an example, a longitudinal case of ALS has been studied using this methodology. It shows that the performance of dynamic articulation quality correlates may be more sensitive and robust than static ones. Conclusions foresee the use of speech as a valuable monitoring methodology for ALS timely evolution.
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