Non intrusive intelligibility predictor for hearing impaired individuals using self supervised speech representations

This is a preprint and may not have undergone formal peer review

Close, G. orcid.org/0000-0002-9478-5421, Hain, T. orcid.org/0000-0003-0939-3464 and Goetze, S. orcid.org/0000-0003-1044-7343 (Submitted: 2023) Non intrusive intelligibility predictor for hearing impaired individuals using self supervised speech representations. [Preprint - arXiv] (Submitted)

Metadata

Item Type: Preprint
Authors/Creators:
Copyright, Publisher and Additional Information:

© 2023 The Author(s). This preprint is made available under a Creative Commons Attribution 4.0 International License. (https://creativecommons.org/licenses/by/4.0/)
Keywords: Clinical Research; Bioengineering; Rehabilitation; Neurosciences; Assistive Technology; Ear
Dates:
  • Submitted: 27 July 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 15 Nov 2023 11:15
Last Modified: 16 Nov 2023 11:21
Status: Submitted
Identification Number: 10.48550/arxiv.2307.13423
Related URLs:
Open Archives Initiative ID (OAI ID):

Download

Export

Statistics


CORE (COnnecting REpositories)