Multiclass audio segmentation based on recurrent neural networks for broadcast domain data

Multiclass audio segmentation based on recurrent neural networks for broadcast domain data

Abstract This paper presents a new approach based on recurrent neural networks (RNN) to the multiclass audio segmentation task whose goal is to classify an audio signal as speech, music, noise or a combination of these. The proposed system is based on the use of bidirectional long short-term Memory...

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Bibliographic Details
Main Authors: Pablo Gimeno, Ignacio Viñals, Alfonso Ortega, Antonio Miguel, Eduardo Lleida
Format: Article
Language:English
Published: SpringerOpen 2020-03-01
Series:EURASIP Journal on Audio, Speech, and Music Processing
Subjects:
Audio segmentation
Recurrent neural networks (RNN)
LSTM
Broadcast data
Online Access:http://link.springer.com/article/10.1186/s13636-020-00172-6

Internet

http://link.springer.com/article/10.1186/s13636-020-00172-6

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