• DocumentCode
    2052759
  • Title

    A database and challenge for acoustic scene classification and event detection

  • Author

    Giannoulis, Dimitrios ; Stowell, Dan ; Benetos, Emmanouil ; Rossignol, Mathias ; Lagrange, Mathieu ; Plumbley, Mark D.

  • Author_Institution
    Centre for Digital Music, Queen Mary Univ. of London, London, UK
  • fYear
    2013
  • fDate
    9-13 Sept. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    An increasing number of researchers work in computational auditory scene analysis (CASA). However, a set of tasks, each with a well-defined evaluation framework and commonly used datasets do not yet exist. Thus, it is difficult for results and algorithms to be compared fairly, which hinders research on the field. In this paper we will introduce a newly-launched public evaluation challenge dealing with two closely related tasks of the field: acoustic scene classification and event detection. We give an overview of the tasks involved; describe the processes of creating the dataset; and define the evaluation metrics. Finally, illustrations on results for both tasks using baseline methods applied on this dataset are presented, accompanied by open-source code.
  • Keywords
    Gaussian processes; acoustic signal processing; feature extraction; mixture models; signal classification; CASA; acoustic scene classification; baseline methods; computational auditory scene analysis; dataset creation; evaluation metrics; event detection; open-source code; public evaluation challenge; Educational institutions; Event detection; Hidden Markov models; Measurement; Music; Speech; Computational auditory scene analysis; acoustic event detection; acoustic scene classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European
  • Conference_Location
    Marrakech
  • Type

    conf

  • Filename
    6811416