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Monitoring ALS from speech articulation kinematics

  • S.I. : Advances in Bio-Inspired Intelligent Systems
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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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Acknowledgments

This work was supported by Calouste Gulbenkian Foundation and the Portuguese Association of ALS (APELA), as well as by Grant TEC2016-77791-C4-4-R (Plan Nacional de I + D+i, Ministry of Economic Affairs and Competitiveness of Spain).

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Correspondence to Pedro Gómez.

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The authors declare that this research has been conducted according to the Helsinki Declaration on ethical standards, it has been carried on public or non-profit funding, and they do not have any conflict of interest regarding the research objectives, procedures and results.

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Gómez, P., Londral, A.R.M., Gómez, A. et al. Monitoring ALS from speech articulation kinematics. Neural Comput & Applic 32, 15801–15812 (2020). https://doi.org/10.1007/s00521-018-3538-6

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  • DOI: https://doi.org/10.1007/s00521-018-3538-6

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