Introduction
The first year of the BioDCASE challenge includes three tasks - Multi-channel audio alignment, marine mammal detection and bioacoustics on tiny hardware. More information about the challenges will be released soon.
Tasks
Multi-Channel Alignment
Researchers often deploy multiple audio recorders simultaneously, for example with passive automated recording units (ARU's) or embedded in animal-borne bio-loggers. Analysing sounds simultaneously captured by multiple recorders can provide insights into animal positions and numbers, as well as the dynamics of communication in groups. However, many of these devices are susceptible to desynchronization due to nonlinear clock drift, which can diminish researchers' ability to glean useful insights. Therefore, a reliable, post-processing-based re-synchronization method would increase usability of collected data.
In this challenge, participants will be presented with pairs of temporally desynchronized recordings and asked to design a system to synchronize them in time. In the development phase, participants will be provided audio pairs and a small set of ground-truth synchronization key points--the likes of which could be produced by a manual review of the data. In the evaluation phase, participants' systems will be ranked by their ability to synchronize unseen audio pairs.
Organizers
Becky Heath
University of Cambridge
Supervised detection of strongly-labelled Antarctic blue and fin whale calls
Passive Acoustic Monitoring (PAM) is a technology used to analyze sounds in the Ocean, where our capacity of visual observation is highly limited. It has emerged as a transformative tool for applied ecology, conservation and biodiversity monitoring. In particular, it offers unique opportunities to examine long-term trends in population dynamics, abundance, distribution and behaviour of different whale species. But for this purpose, the automation of PAM data processing, involving the automatic detection of whale calls in long-term recordings, faces two major issues: the scarcity of calls and the variability of soundscapes.
In this data challenge, a supervised sound event detection task was designed, and applied to the detection of 7 different call types from two emblematic whale species, the Antarctic blue and fin whales. This task aims to improve and assess the ability of models to address the two issues just mentioned, as models will have to deal with whale calls happening only 6 % of the time, and PAM recordings coming from different time periods and sites all around Antarctica that present highly variable soundscapes. The White Continent appeared to be a very exciting playground to start a large-scale evaluation of model generalization capacity, but challenging for sure!
Organizers
Olivier Adam
Sorbonne Université, LAM
Paul Carvaillo
France Energies Marines
Anatole Gros-Martial
Centre d’Etudes Biologiques de Chizé, GEO-Ocean
Lucie Jean-Labadye
Sorbonne Université, LAM
Brian Miller
Australian Antarctic Division
Paul Nguyen Hong Duc
Curtin University
Pierre-Yves le Rolland Raumer
IUEM
Bioacoustics for Tiny Hardware
The next generation of autonomous recording units contains programmable chips, thus offering the opportunity to perform BioDCASE tasks. On-device processing has multiple advantages, such as high durability, low latency, and privacy preservation. However, such “tiny hardware” is limited in terms of memory and compute, which calls for the development of original methods in audio content analysis. In this context, task participants will revisit the well-known problem of automatic detection of birdsong while adjusting their systems so as to meet the specifications of a commercially available microcontroller.
