Few-shot bioacoustic event detection at the DCASE 2023 challenge
Ines Nolasco Burooj Ghani Shubhr Singh Ester Vidaña-Vila Helen Whitehead Emily Grout Michael Emmerson Frants Jensen Ivan Kiskin Joe Morford Ariana Strandburg-Peshkin Lisa Gill Hanna Pamuła Vincent Lostanlen Dan Stowell
Few-shot bioacoustic event detection consists in detecting sound events of
specified types, in varying soundscapes, while having access to only a few
examples of the class of interest. This task ran as part of the DCASE challenge
for the third time this year with an evaluation set expanded to include new
animal species, and a new rule: ensemble models were no longer allowed. The
2023 few shot task received submissions from 6 different teams with F-scores
reaching as high as 63% on the evaluation set. Here we describe the task,
focusing on describing the elements that differed from previous years. We also
take a look back at past editions to describe how the task has evolved. Not
only have the F-score results steadily improved (40% to 60% to 63%), but the
type of systems proposed have also become more complex. Sound event detection
systems are no longer simple variations of the baselines provided: multiple
few-shot learning methodologies are still strong contenders for the task.