Adaptive Loss Balancing for Multi-Task Bioacoustic Classification of Bird Species and Call Types
Reliable analysis of bird vocalisations in passive acoustic monitoring requires models handling multiple, imbalanced annotation targets. We extend BirdCallNet for joint species and call-type classification on the long-tailed WiWa dataset and investigate how task-loss balancing interacts with pretrained representations and adaptation depth. We evaluate four bird-domain encoders, ConvNeXtBS, EAT, BirdMAE, and ProtoCLR, with separate species and call-type heads under linear probing, attentive probing, and full fine-tuning. A manually tuned fixed objective is compared with homoscedastic uncertainty weighting and Dynamic Weight Averaging across all three adaptation regimes, while GradNorm is e...
| Authors | Paria Vali Zadeh, Sven Tomforde |
|---|---|
| Primary category | cs.SD |
| Published | 3 July 2026 |
| Last updated at source | 3 July 2026 |
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