Forum Acusticum 2026

Session

A02.00 Bio-acoustics

A02.00

8 Sept 2026, 13:20

Conveners

A02.00 Bio-acoustics: S007

• Angela Stöger-Horwath (University of Vienna, Vienna Zoo)
• Paolo Diviacco
• Dick Botteldooren (U-Ghent)
• Michael Kerscher

A02.00 Bio-acoustics: P421

• Paolo Diviacco
• Michael Kerscher
• Angela Stöger-Horwath (University of Vienna, Vienna Zoo)
• Dick Botteldooren (U-Ghent)

3822. Detecting Redwing (Turdus iliacus) Flight Calls in Passive Acoustic Recordings of Nocturnal Migration (FA2026/589)

Paul Devos (Ghent University)

08/09/2026, 13:20

A02 Bio-acoustics

Bird migration is the seasonal movement of birds between regions, often influenced by weather, food availability, and breeding needs. Passive acoustic monitoring (PAM) provides a useful way to study bird migration by recording the calls of birds passing through an area. These calls are often short and can be difficult to detect, especially when recordings contain environmental noise,...

3823. Sonic Selva: Calibrated Ambisonic and Binaural Soundscape Baselines of Venezuelan Biotopes (FA2026/287)

Marc-Laurin Schimke (TU Berlin)

08/09/2026, 13:40

A02 Bio-acoustics

The preservation of highly biodiverse acoustic environments is of critical importance given the rapid global decline of natural ecosystems. This paper presents Sonic Selva, an open-access, spatial audio dataset that captured the acoustic baselines of Venezuelan rainforests and savannas in 2024. A calibrated industrial binaural measurement system (HEAD acoustics SQobold with BHS II) and a...

3826. bacpipe: a Python package to make bioacoustic deep learning models accessible (FA2026/732)

Vincent S. Kather (Naturalis Biodiversity Center)

08/09/2026, 14:00

A02 Bio-acoustics

Natural sounds have been recorded for millions of hours over the previous decades using passive acoustic monitoring. Improvements in deep learning models have vastly accelerated the analysis of large portions of this data. While new models advance the state-of-the-art, accessing them using tools to harness their full potential is not always straightforward. Here we present bacpipe, a...

3827. Characterisation of Asian hornet flight sounds (FA2026/853)

Jan Vandoorne (KU Leuven)

08/09/2026, 14:00

A02 Bio-acoustics

The invasive Asian hornet (Vespa velutina) poses a threat to insect biodiversity, pollination services, and honey production. Current control strategies rely on locating and destroying nests. One method to locate nests is by using a wick bait station and recording return times of hornets, which allows an estimation of nest distance to the station. This approach could potentially be automated...

3824. Sector-based Filtering and CLEAN-SC Beamforming for Natural Soundscape Analysis : the case of the Little Owl (FA2026/403)

Maud Biscarat (LMFA UMR 5509 CNRS, Ecole Centrale de Lyon)

08/09/2026, 14:00

A02 Bio-acoustics

Acoustic monitoring has become a widely used approach to study ecosystems. However, the large amount of acquired data requires fast processing techniques to efficiently analyze soundscapes. For that, sound detection and classification algorithms, such as BirdNET, have been developed. However, the performance of BirdNET, quantified by the confidence score, is closely linked to the...

3825. Passive acoustic filtering for automatic insect monitoring (FA2026/814)

Jef Morlion (KU Leuven)

08/09/2026, 14:20

A02 Bio-acoustics

Automated signaling of pest insects in the field could drastically improve the cost-effectiveness of integrated pest management. Acoustic monitoring of flying insects has the potential to be a low cost solution with spatio-temporal resolution for timely intervention. However, it is not used in practice due to high background noise levels, which obfuscate the insect sounds.We propose an...