Environment-Aware Knowledge Distillation for Improved Resource-Constrained Edge Speech Recognition
Recent advances in self-supervised learning have allowed automatic speech recognition (ASR) systems to achieve state-of-the-art (SOTA) word error rates (WER) while requiring only a fraction of the labeled data needed by its predecessors. Notwithstanding, while such models achieve SOTA results in mat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/23/12571 |