Detection and classification of acoustic scenes and events: An IEEE AASP challenge

Abstract

This paper describes a newly-launched public evaluation challenge on acoustic scene classification and detection of sound events within a scene. Systems dealing with such tasks are far from exhibiting human-like performance and robustness. Undermining factors are numerous: the extreme variability of sources of interest possibly interfering, the presence of complex background noise as well as room effects like reverberation. The proposed challenge is an attempt to help the research community move forward in defining and studying the aforementioned tasks. Apart from the challenge description, this paper provides an overview of systems submitted to the challenge as well as a detailed evaluation of the results achieved by those systems.

DOI: 10.1109/WASPAA.2013.6701819

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@article{Giannoulis2013DetectionAC, title={Detection and classification of acoustic scenes and events: An IEEE AASP challenge}, author={Dimitrios Giannoulis and Emmanouil Benetos and Dan Stowell and Mathias Rossignol and Mathieu Lagrange and Mark D. Plumbley}, journal={2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics}, year={2013}, pages={1-4} }