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A Multi-Channel Fusion Framework for Audio Event Detection

Phan, Huy, Maass, Marco, Hertel, Lars, Mazur, Radoslaw, Mertins, Alfred (2015) A Multi-Channel Fusion Framework for Audio Event Detection. In: IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA 2015). . pp. 1-5. IEEE, New York, USA ISBN 978-1-4799-7450-4. (doi:10.1109/WASPAA.2015.7336889) (KAR id:72689)

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We propose in this paper a simple, yet efficient multi-channel fusion framework for joint acoustic event detection and classification. The joint problem on individual channels is posed as a regression problem to estimate event onset and offset positions. As an intermediate result, we also obtain the posterior probabilities which measure the confidence that event onsets and offsets are present at a temporal position. It facilitates the fusion problem by accumulating the posterior probabilities of different channels. The detection hypotheses are then determined based on the summed posterior probabilities. While the proposed fusion framework appears to be simple and natural, it significantly outperforms all the single-channel baseline systems on the ITC-Irst database. We also show that adding channels one by one into the fusion system yields performance improvements, and the performance of the fusion system is always better than those of the individual-channel counterparts.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/WASPAA.2015.7336889
Uncontrolled keywords: Acoustic event detection, classification, multi-channel fusion, regression forests
Divisions: Faculties > Sciences > School of Computing
Depositing User: Huy Phan
Date Deposited: 25 Feb 2019 16:33 UTC
Last Modified: 03 Jun 2019 09:28 UTC
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