A comparative evaluation of lab-generic and site-specific impulse response-based beamforming for enhanced automated bird call detection

Automated ecoacoustic monitoring supports biodiversity conservation but struggles with signal degradation in noisy forests. Microphone-array recorders enable beamforming to focus on target directions and reduce background noise, yet their effectiveness in autonomous settings remains underexplored. This study evaluates filter-and-sum beamforming using measured impulse responses (IRs) to enhance bird-call classification. It compares lab-generic IRs from a semi-anechoic chamber with site-specific IRs measured in a forest. Playback experiments were conducted with a multichannel autonomous recorder using Eurasian blue tit calls in a real forest (1 to 64 m) and a 31-speaker virtual soundscape (signal-to-noise ratios from +30 to -30 dB). BirdNET performed classification, with metrics including detection count and confidence improvements versus the omnidirectional baseline. Both beamforming methods outperformed the baseline. Site-specific IR beamforming excelled at intermediate and long ranges. Both significantly raised confidence scores (p < 0.001), with site-specific IRs showing a modest advantage (mean Δ confidence 0.15 vs 0.11; p = 0.00001). These results confirm the value of beamforming for passive acoustic monitoring: site-specific IRs perform best, while lab-generic IRs provide a robust alternative for large-scale use.