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IEEE AASP Challenge:
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We invite researchers in signal processing, machine learning and other fields to participate in our challenge, which consists of a set of related tasks on automatic detection and classification of acoustic scenes and acoustic events.
The tasks fall into the field of computational auditory scene analysis (CASA). Humans are able to follow specific sound sources in a complex audio environment with ease and the development of systems that try to mimic this behaviour is an open problem, especially in the case of overlapping sound events.
The deadline for confirming participation to the challenge is 31st March 2013 (please send an email to aasp-challenge-owner@eecs.qmul.ac.uk with participant names/affiliations). The deadline for code submission is 14th April 2013.
Results will be presented at a special session in WASPAA 2013; participants are invited to present a poster at a special session. Also, authors of novel work are encouraged to submit their work as a regular paper at WASPAA 2013.
In order to participate in the discussion phase and to receive news about the challenge, please subscribe to the aasp-challenge mailing list.
The extended abstracts provide the outside world with a general understanding of what each submission is trying to accomplish. The extended abstracts need NOT be cutting edge/never-before-published materials. Participants are encouraged to submit novel work as a regular paper at the WASPAA 2013 conference.
The extended abstracts can be revised by the authors after the results have been announced. We will post the final versions of the extended abstracts in the challenge website. The challenge abstracts:
This challenge is organised by the Centre for Digital Music and by IRCAM, under the auspices of the Audio and Acoustic Signal Processing (AASP) technical committee of the IEEE Signal Processing Society. Click here for the original challenge proposal document.
The organisers, Dimitrios Giannoulis (QMUL), Emmanouil Benetos (City/QMUL), Dan Stowell (QMUL), Mathias Rossignol (IRCAM), Mathieu Lagrange (IRCAM) and Mark D. Plumbley (QMUL)