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Exploring convolutional, recurrent, and hybrid deep neural networks for speech and music detection in a large audio dataset
Abstract Audio signals represent a wide diversity of acoustic events, from background environmental noise to spoken communication. Machine learning models such as neural networks have already been proposed for audio signal modeling, where recurrent structures can take advantage of temporal dependenc...
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| Główni autorzy: | , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
SpringerOpen
2019-06-01
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| Seria: | EURASIP Journal on Audio, Speech, and Music Processing |
| Hasła przedmiotowe: | |
| Dostęp online: | http://link.springer.com/article/10.1186/s13636-019-0152-1 |
| Etykiety: |
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