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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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
| Published: |
2024
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| Online Access: | https://eprints.nottingham.ac.uk/77884/ |