DocumentCode :
729736
Title :
Early event detection in audio streams
Author :
Huy Phan ; Maass, Marco ; Mazur, Radoslaw ; Mertins, Alfred
Author_Institution :
Inst. for Signal Process., Univ. of Lubeck, Lubeck, Germany
fYear :
2015
fDate :
June 29 2015-July 3 2015
Firstpage :
1
Lastpage :
6
Abstract :
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.
Keywords :
audio signal processing; audio streaming; signal detection; ITC-Irst database; audio event detection; audio streams; continuous audio recordings; detection error rate; early event detection; Accuracy; Databases; Estimation; Event detection; Reliability; Training; Vegetation; Early detection; audio event detection; online detection; regression forests;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo (ICME), 2015 IEEE International Conference on
Conference_Location :
Turin
Type :
conf
DOI :
10.1109/ICME.2015.7177439
Filename :
7177439
Link To Document :
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