Name
Abstract | ||
|---|---|---|
Patients affected by amyotrophic lateral sclerosis (ALS) show specific dysarthria in their speech resulting in specific marks which 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 depending on the dynamic behaviour of speech. Specifically, distribution functions from the absolute kinematic velocity estimated on 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, several cases of ALS were studied longitudinally using this methodology. The study shows that the performance of dynamic articulation quality correlates may be sensitive and robust in tracking illness progress. Conclusions foresee the use of speech as a valuable monitoring methodology for ALS timely neurodegenerative progression.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s00521-018-3538-6 | Neural Computing and Applications |
Keywords | DocType | Volume |
Amyotrophic lateral sclerosis, Neuromotor diseases, Kullback–Leibler divergence, Speech articulation | Journal | 32 |
Issue | ISSN | Citations |
20 | 1433-3058 | 0 |
PageRank | References | Authors |
0.34 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pedro Gómez | 1 | 1 | 1.06 |
| Ana Rita Londral | 2 | 112 | 30.69 |
| Ana Rita Londral | 3 | 112 | 30.69 |
| Andrés Gómez | 4 | 1 | 1.06 |
| Daniel Palacios | 5 | 0 | 1.01 |
| V. Rodellar | 6 | 14 | 7.98 |