GetNetUPAM: Ecologically Informed Nested Cross-Validation and Noise-Robust Attention for Marine Bioacoustic Monitoring
arXiv:2509.04682v2 Announce Type: replace-cross Abstract: Deploying reliable bioacoustic monitoring systems requires models that generalize under high-noise, low-SNR conditions and evaluation protocols that expose deployment-relevant failure modes, gaps largely unaddressed in current UPAM practice. Intrinsic noise, variable propagation, and mixed biological and anthropogenic sources induce distribution shifts that conventional models and single-split evaluations obscure, inflating performance and masking instability. We introduce GetNetUPAM, a hierarchical nested cross-validation framework tha
The increasing deployment of bioacoustic monitoring systems highlights the critical need for noise-robust and reliable models, a gap this research aims to address.
Improving the accuracy and robustness of bioacoustic monitoring in noisy, real-world conditions enhances our ability to track and understand marine ecosystems, crucial for environmental protection and resource management.
The introduction of GetNetUPAM and its nested cross-validation framework changes how bioacoustic monitoring systems are evaluated and developed, leading to more resilient and generalizable models.
- · Environmental monitoring agencies
- · Marine biologists
- · AI researchers in acoustic analysis
- · Conservation organizations
- · Developers of less robust monitoring systems
- · Organizations relying on simple evaluation metrics
More accurate and reliable detection of marine species and anthropogenic noise in challenging environments.
Improved policy decisions and conservation efforts based on higher-fidelity environmental data.
Enhanced understanding of long-term ecological trends and the impact of human activities on marine life, potentially leading to new regulatory frameworks or technological solutions for noise reduction.
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Read at arXiv cs.AI