Exploring convolutional, recurrent, and hybrid deep neural networks for speech and music detection in a large audio dataset
The version of record of this article, first published in EURASIP Journal on Audio, Speech, and Music Processing, is available online at Publisher’s website: http://dx.doi.org/10.1186/s13636-019-0152-1
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/690573 |
| Acceso en línea: | http://hdl.handle.net/10486/690573 https://dx.doi.org/10.1186/s13636-019-0152-1 |
| Access Level: | acceso abierto |
| Palabra clave: | Acoustic event detection Music activity detection Neural networks Convolutional networks LSTM Speech activity detection Telecomunicaciones |
| Sumario: | The version of record of this article, first published in EURASIP Journal on Audio, Speech, and Music Processing, is available online at Publisher’s website: http://dx.doi.org/10.1186/s13636-019-0152-1 |
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