Learning to Detect Dysarthria from Raw Speech-Reference-Cited by-同舟云学术

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Learning to Detect Dysarthria from Raw Speech

Published:2019-05 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Millet Juliette,Zeghidour Neil

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8671773/8682151/08682324.pdf?arnumber=8682324

Cited by 28 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Exploring the Impact of Fine-Tuning the Wav2vec2 Model in Database-Independent Detection of Dysarthric Speech;IEEE Journal of Biomedical and Health Informatics;2024-08

2. Automatic dysarthria detection and severity level assessment using CWT-layered CNN model;EURASIP Journal on Audio, Speech, and Music Processing;2024-06-25

3. HPO Based Enhanced Elman Spike Neural Network for Detecting Speech of People with Dysarthria;Optical Memory and Neural Networks;2024-06

4. Harnessing Deep Learning Techniques for Dysarthria Detection;2024 Third International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS);2024-03-14

5. Dysarthria Diagnosis and Dysarthric Speaker Identification Using Raw Speech Model;2024 National Conference on Communications (NCC);2024-02-28

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