DocumentCode :
2535478
Title :
Strategies for orca call retrieval to support collaborative annotation of a large archive
Author :
Ness, Steven R. ; Lerch, Alex ; Tzanetakis, George
Author_Institution :
Comput. Sci., Univ. of Victoria, Victoria, BC, Canada
fYear :
2011
fDate :
17-19 Oct. 2011
Firstpage :
1
Lastpage :
6
Abstract :
The Orchive is a large audio archive of hydrophone recordings of Killer whale (Orcinus orca) vocalizations. Researchers and users from around the world can interact with the archive using a collaborative web-based annotation, visualization and retrieval interface. In addition a mobile client has been written in order to crowdsource Orca call annotation. In this paper we describe and compare different strategies for the retrieval of discrete Orca calls. In addition, the results of the automatic analysis are integrated in the user interface facilitating annotation as well as leveraging the existing annotations for supervised learning. The best strategy achieves a mean average precision of 0.77 with the first retrieved item being relevant 95% of the time in a dataset of 185 calls belonging to 4 types.
Keywords :
audio signal processing; hydrophones; information retrieval; learning (artificial intelligence); user interfaces; Killer whale vocalizations; audio archive; collaborative Web-based annotation; collaborative annotation; crowdsource Orca call annotation; hydrophone recordings; mobile client; orca call retrieval; retrieval interface; supervised learning; user interface; Collaboration; Correlation; Games; Mobile communication; Noise measurement; Sonar equipment; Whales;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Signal Processing (MMSP), 2011 IEEE 13th International Workshop on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4577-1432-0
Electronic_ISBN :
978-1-4577-1433-7
Type :
conf
DOI :
10.1109/MMSP.2011.6093798
Filename :
6093798
Link To Document :
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