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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Bibliografiska uppgifter
Huvudupphovsmän: Diego de Benito-Gorron, Alicia Lozano-Diez, Doroteo T. Toledano, Joaquin Gonzalez-Rodriguez
Materialtyp: Artigo
Språk:Inglês
Publicerad: SpringerOpen 2019-06-01
Serie:EURASIP Journal on Audio, Speech, and Music Processing
Ämnen:
Acoustic event detection
Speech activity detection
Music activity detection
Neural networks
Convolutional networks
LSTM
Länkar:http://link.springer.com/article/10.1186/s13636-019-0152-1
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