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Capsule Routing for Sound Event Detection

Iqbal, Turab, Xu, Yong, Kong, Qiuqiang and Wang, Wenwu (2018) Capsule Routing for Sound Event Detection In: 26th European Signal Processing Conference (EUSIPCO 2018), 3 - 7 September 2018, Rome, Italy.

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Abstract

The detection of acoustic scenes is a challenging problem in which environmental sound events must be detected from a given audio signal. This includes classifying the events as well as estimating their onset and offset times. We approach this problem with a neural network architecture that uses the recentlyproposed capsule routing mechanism. A capsule is a group of activation units representing a set of properties for an entity of interest, and the purpose of routing is to identify part-whole relationships between capsules. That is, a capsule in one layer is assumed to belong to a capsule in the layer above in terms of the entity being represented. Using capsule routing, we wish to train a network that can learn global coherence implicitly, thereby improving generalization performance. Our proposed method is evaluated on Task 4 of the DCASE 2017 challenge. Results show that classification performance is state-of-the-art, achieving an Fscore of 58.6%. In addition, overfitting is reduced considerably compared to other architectures.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Iqbal, Turabt.iqbal@surrey.ac.uk
Xu, Yongyong.xu@surrey.ac.uk
Kong, Qiuqiangq.kong@surrey.ac.uk
Wang, WenwuW.Wang@surrey.ac.uk
Date : 3 December 2018
DOI : 10.23919/EUSIPCO.2018.8553198
Copyright Disclaimer : Copyright 2018 EURASIP. Published by IEEE.
Uncontrolled Keywords : Routing; Neural networks; Feature extraction; Task analysis; Convolution; Event detection
Related URLs :
Depositing User : Melanie Hughes
Date Deposited : 21 Jun 2018 13:49
Last Modified : 13 Dec 2018 16:10
URI: http://epubs.surrey.ac.uk/id/eprint/847120

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