Automated Dysarthria Severity Classification: A Study on Acoustic Features and Deep Learning Techniques
Assessing the severity level of dysarthria can provide an insight into the patient’s improvement, assist pathologists to plan therapy, and aid automatic dysarthric speech recognition systems. In this article, we present a comparative study on the classification of dysarthria severity leve...
Main Authors: | Amlu Anna Joshy, Rajeev Rajan |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9762324/ |
Similar Items
-
Orofacial Muscle Strength across the Dysarthrias
by: Heather M. Clark, et al.
Published: (2022-03-01) -
Artificial Intelligence‐Powered Acoustic Analysis System for Dysarthria Severity Assessment
by: Zhenglin Zhang, et al.
Published: (2023-10-01) -
The Detection of Dysarthria Severity Levels Using AI Models: A Review
by: Afnan Al-Ali, et al.
Published: (2024-01-01) -
Acoustic Study of Second-Formant Transition in Flaccid Dysarthria
by: Faezeh Abdolahi, et al.
Published: (2017-02-01) -
Acoustic Identification of Sentence Accent in Speakers with Dysarthria: Cross-Population Validation and Severity Related Patterns
by: Viviana Mendoza Ramos, et al.
Published: (2021-10-01)