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Early Event Detection in Audio Streams

Phan, Huy, Maass, Marco, Mazur, Radoslaw, Mertins, Alfred (2015) Early Event Detection in Audio Streams. In: IEEE International Conference on Multimedia and Expo (ICME 2015). . pp. 1-6. IEEE, Torino, Italy E-ISBN 978-1-4799-7082-7. (doi:10.1109/ICME.2015.7177439) (KAR id:72685)

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Audio event detection has been an active field of research in recent years. However, most of the proposed methods, if not all, analyze and detect complete events and little attention has been paid for early detection. In this paper, we present a system which enables early audio event detection in continuous audio recordings in which an event can be reliably recognized when only a partial duration is observed. Our evaluation on the ITC-Irst database, one of the standard database of the CLEAR 2006 evaluation, shows that: on one hand, the proposed system outperforms the best baseline system by 16% and 8% in terms of detection error rate and detection accuracy respectively; on the other hand, even partial events are enough to achieve the performance that is obtainable when the whole events are observed.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/ICME.2015.7177439
Uncontrolled keywords: Early detection, audio event detection, online detection, regression forests
Divisions: Faculties > Sciences > School of Computing
Depositing User: Huy Phan
Date Deposited: 25 Feb 2019 16:53 UTC
Last Modified: 03 Jun 2019 09:28 UTC
Resource URI: (The current URI for this page, for reference purposes)
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