Towards end-to-end speech recognition with transfer learning
Abstract A transfer learning-based end-to-end speech recognition approach is presented in two levels in our framework. Firstly, a feature extraction approach combining multilingual deep neural network (DNN) training with matrix factorization algorithm is introduced to extract high-level features. Se...
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| Hauptverfasser: | , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
SpringerOpen
2018-11-01
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| Schriftenreihe: | EURASIP Journal on Audio, Speech, and Music Processing |
| Schlagworte: | |
| Online-Zugang: | http://link.springer.com/article/10.1186/s13636-018-0141-9 |
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