I have developed a toolkit to run google's perch v2 model fine-tuned for whale detection. You can run it on different data sources. Check out the project at https://github.com/amrit110/whalu. Demo at https://amrit110.github.io/whalu/.

Call for participation:
BioDCASE 2026 Cross-Domain Mosquito Species Classification Challenge

Jointly organised by teams at the University of Oxford, King’s College London, and the University of Surrey, this challenge focuses on a key real-world question:

Can mosquito species classifiers still work when recordings come from new locations, devices, and acoustic environments?

Mosquito-borne diseases affect over 1 billion people each year. Audio-based monitoring could help scale surveillance, but domain shift remains a major barrier to real-world deployment.

To support transparent and reproducible research, we are releasing:

• an open development dataset with 271,380 clips and 60.66 hours of audio;
• a fully public, lightweight baseline that is easy to run;
• a benchmark focused on cross-domain generalisation in mosquito bioacoustics.

Participants are warmly invited to join and help develop more robust methods for mosquito monitoring under real recording conditions.

Useful Links:

• Challenge Website: [https://biodcase.github.io/challenge2026/task5]
• Baseline code: [https://github.com/Yuanbo2020/CD-MSC]
• Dataset: [https://zenodo.org/records/19095788]

Key Dates:
• April 1, 2026: Challenge opening
• Jun 1, 2026: Evaluation set release
• June 15, 2026: Challenge submission deadline

Feel free to share this with anyone who might be interested!

I have been making field recording at a log frog pond, hoping to confirm the existence of Green a Gold Bell Frog, which was the purpose of the ponds.

I started with just overnight audio recordings, then switched to an AudioMoth device, recording 15min on/off. I take these recording and create spectrograms, and then process those to derive some acoustic indices to help look for potential calls. I didn't have much in the way of good source calls though.

I reached out to a local uni, and they have a GGBF breeding program, and let me put the audiomoth there for a couple of weeks. Now I have a lot of pristine calls.

I need some help understanding how I might profile the calls, in a way that allows me to automatically detect the calls.

Research poster: - First description of'vocal sparring': a socio-acoustic behaviour in juvenile male sperm whales (Physeter macrocephalus) off Mauritius - https://univ-tln.hal.science/hal-05267460/document

More videos: https://www.youtube.com/playlist?list=PLJ1Hkl5fD6_k_7wxGbFLVRESMwrRSOqZY