Static and Dynamic Source and Filter Cues for Classification of Amyotrophic Lateral Sclerosis Patients and Healthy Subjects

Bhattacharjee, T and Thirumala Kumar, CV and Belur, Y and Nalini, A and Yadav, R and Ghosh, PK (2023) Static and Dynamic Source and Filter Cues for Classification of Amyotrophic Lateral Sclerosis Patients and Healthy Subjects. In: UNSPECIFIED.

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Abstract

Dysarthria due to Amyotrophic Lateral Sclerosis (ALS) affects speech production. Even the elementary sustained vowel utterances get impaired. For these, the impairments can be in achieving vowel-specific articulatory configurations, reflected in static acoustic cues, and/or in sustaining a configuration for a prolonged duration, reflected in dynamic cues. Such cues can further be attributed to the vocal cord (source) and vocal tract (filter) involved in speech production. This paper analyzes the relative contributions of these static (captured through average spectral characteristics) and dynamic (captured through spectral variations over time) source and filter cues toward automatic classification of ALS patients and healthy subjects using sustained utterances of /a/, /i/, /o/ and /u/. Experiments with 80 ALS patients and 80 healthy subjects suggest that the source cues (static/dynamic) are not the primary discriminators. For /i/, the static filter cues achieve the highest mean classification accuracy of 76.66, whereas, for /a/, /o/ and /u/, the dynamic filter attributes contribute the most attaining average accuracies of 66.29, 73.03 and 70.27, respectively. Hence, ALS patients seem to face difficulties in forming the front closed vocal tract structure of /i/, whereas, holding the target vocal tract shape for long appears to be the primary challenge in case of /a/, /o/ and /u/. © 2023 IEEE.

Item Type:	Conference Paper
Publication:	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	04 Mar 2024 07:21
Last Modified:	04 Mar 2024 07:21
URI:	https://eprints.iisc.ac.in/id/eprint/84281

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