MLLab at DCASE 2022
On 3-4 November, several Machine Listening Lab researchers will participate at the 7th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE 2022). The workshop aims to provide a venue for researchers working on computational analysis of sound events and scene analysis to present and discuss their results, and is organised in conjunction with the DCASE 2022 Challenge.
As in previous years, the Machine Listening Lab will have a strong presence at the workshop, both in terms of numbers and overall impact. The below papers presented at DCASE 2022 are authored or co-authored by MLLab members:
- Few-shot bioacoustic event detection: enhanced classifiers for prototypical networks, by Ren Li, Jinhua Liang, Huy Phan
- Leveraging label hierarchies for few-shot everyday sound recognition, by Jinhua Liang, Huy Phan, Emmanouil Benetos
- Few-shot bioacoustic event detection at the DCASE 2022 challenge, by Ines Nolasco, Dan Stowell, Vincent Lostanlen, Shubhr Singh, Veronica Morfi, Ari Strandburg-Peshkin, Lisa Gill, Emily Grout, Ester Vidana-Villa, Joe Morford, Michael Emmerson, Frants Jensen, Helen Whitehead, Hanna Pamula, Ivan Kiskin
- Explaining the decisions of anomalous sound detectors, by Kimberly T. Mai, Toby Davies, Lewis D. Griffin, Emmanouil Benetos
On challenge organisation, MLLab PhD students Inês Nolasco and Shubhr Singh, MLLab alumna and research visitor Veronica Morfi, and MLLab alumnus Dan Stowell are all involved in the organisation of the DCASE 2022 Challenge task on Few-shot Bioacoustic Event Detection, focusing on sound event detection in a few-shot learning setting for animal (mammal and bird) vocalisations.
See you all at DCASE!