Addressing Data Scarcity in Voice Disorder Detection with Self-Supervised Models-Reference-Cited by-同舟云学术

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Addressing Data Scarcity in Voice Disorder Detection with Self-Supervised Models

Published:2024-04-14 Issue: Volume:33 Page:11866-11870
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Gupta Rijul¹,Madill Catherine²,Gunjawate Dhanshree R.²,Nguyen Duy Duong²,Jin Craig T.¹

Affiliation:

1. The University of Sydney,Computing and Audio Research Laboratory, School of Electrical and Information Engineering,Australia

2. The University of Sydney,Voice Research Laboratory, Sydney School of Health Sciences, Faculty of Medicine and Health,Australia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10446075.pdf?arnumber=10446075

Reference33 articles.

1. Voice Disorders in the General Population: Prevalence, Risk Factors, and Occupational Impact

2. The Spectrum of Vocal Dysfunction

3. Diagnostic accuracy of history, laryngoscopy, and stroboscopy

4. Saarbruecken voice database;Woldert-Jokisz;Institut für Phonetik, Universität des Saarlandes,2007

5. A new database of healthy and pathological voices

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