Self-supervised learning for automatic speech recognition In low-resource environments

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Self-supervised learning for automatic speech recognition In low-resource environments

Supervised deep neural networks trained with substantial amounts of annotated speech data have demonstrated impressive performance across a spectrum of spoken language processing applications, frequently establishing themselves as the leading models in respective competitions. Nonetheless, a signifi...

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Bibliographic Details
Main Author:	Fatehi, Kavan
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2024
Subjects:	Automatic Speech Recognition Low-resource Environment Self-Supervised Learning
Online Access:	https://eprints.nottingham.ac.uk/77884/

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