Acoustic classification of multiple simultaneous bird species: a multi-instance multi-label approach.

@article{Briggs2012AcousticCO,
  title={Acoustic classification of multiple simultaneous bird species: a multi-instance multi-label approach.},
  author={Forrest Briggs and Balaji Lakshminarayanan and Lawrence Neal and Xiaoli Z. Fern and Raviv Raich and Sarah Hadley and Adam S. Hadley and Matthew G. Betts},
  journal={The Journal of the Acoustical Society of America},
  year={2012},
  volume={131 6},
  pages={
          4640-50
        }
}
Although field-collected recordings typically contain multiple simultaneously vocalizing birds of different species, acoustic species classification in this setting has received little study so far. This work formulates the problem of classifying the set of species present in an audio recording using the multi-instance multi-label (MIML) framework for machine learning, and proposes a MIML bag generator for audio, i.e., an algorithm which transforms an input audio signal into a bag-of-instances… 
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