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This paper is in the following e-collection/theme issue:

Emerging Technologies for Rehabilitation (503) Digital Health Reviews (3658) Natural Language Processing (1277) Linguistics, Comprehension, and Learning (60) Speech and Phonetics in Verbal Protocols (Think Aloud, Recall, and Explanation Tasks) (94)

Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44489, first published .
Man gesturing while talking to woman in cafe

Models and Approaches for Comprehension of Dysarthric Speech Using Natural Language Processing: Systematic Review

Models and Approaches for Comprehension of Dysarthric Speech Using Natural Language Processing: Systematic Review

Authors of this article:

Benard Alaka1 Author Orcid Image ;   Bernard Shibwabo1 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

Journals

  1. Chenain L, Riad R, Fraisse N, Jubin C, Morgado G, Youssov K, Lunven M, Bachoud-Levi A. Graph methods to infer spatial disturbances: Application to Huntington's Disease's speech. Cortex 2024;176:144 View
  2. Kotangale K, Parkale Y. A Novel Hybrid Deep Learning Model Optimized by Pelican Algorithm for Robust Dysarthric Speech Classification with Multi-feature Fusion and Attention-GAN. Circuits, Systems, and Signal Processing 2026;45(5):4055 View

Conference Proceedings

  1. Hashan A, Dmitrievich C, Valerievich M, Vasilyevich D, Alexandrovich K, Andreevich B. 2024 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). Deep Learning Based Speech Recognition for Hyperkinetic Dysarthria Disorder View
  2. Li B, Yao F, Wang Y. Proceedings of the 2026 2nd International Conference on Artificial Intelligence and Computational Intelligence. Research on Whisper Speech Recognition for Dysarthric Speakers View