Assessment of Dysarthria Using One-Word Speech Recognition with Hidden Markov Models-Reference-Cited by-同舟云学术

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Assessment of Dysarthria Using One-Word Speech Recognition with Hidden Markov Models

Published:2019 Issue:13 Volume:34 Page:
ISSN:1011-8934
Container-title:Journal of Korean Medical Science
language:en
Short-container-title:J Korean Med Sci

Author:

Lee Seung Hak¹²^ORCID,Kim Minje³^ORCID,Seo Han Gil¹^ORCID,Oh Byung-Mo¹^ORCID,Lee Gangpyo²^ORCID,Leigh Ja-Ho²⁴⁵^ORCID

Affiliation:

1. Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.

2. Department of Rehabilitation Medicine, Incheon Workers' Compensation Hospital, Incheon, Korea.

3. Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA.

4. Department of Rehabilitation Medicine, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Incheon, Korea.

5. Institute of Public Health and Medical Service, Seoul National University Hospital, Seoul, Korea.

Funder

Korea Workers' Compensation and Welfare Service

Publisher

Korean Academy of Medical Sciences

Subject

General Medicine

Link

https://synapse.koreamed.org/pdf/10.3346/jkms.2019.34.e108

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1. Reviewing the Horizon: The Future of Extended Reality and Artificial Intelligence in Neurorehabilitation for Brain Injury Recovery;Information;2024-08-21

2. A Strategic Approach for Robust Dysarthric Speech Recognition;Wireless Personal Communications;2024-02

3. The Detection of Dysarthria Severity Levels Using AI Models: A Review;IEEE Access;2024

4. Pareto-Optimized Non-Negative Matrix Factorization Approach to the Cleaning of Alaryngeal Speech Signals;Cancers;2023-07-16

5. Dysarthric Speech Transformer: A Sequence-to-Sequence Dysarthric Speech Recognition System;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2023

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