157 citations · 233 across the 12 of their papers we have counts for
13 papers
Effects of interpulse-interval variation on deep-learning classification of bat vocalizations
Welmoed R. Eversteijn, Burooj Ghani, A. Leonie Baier +1
Temporal context may aid automated bat-species classification, but the contribution of specific features remains unclear. We investigated whether variation in the interpulse interv…
ChiroEcho: extending automated bat vocalisation classification beyond the learned taxonomy
Burooj Ghani, Welmoed Eversteijn, Milan van Hirtum +4
Bats are key indicators of ecosystem health and are protected throughout Europe, making reliable population monitoring a conservation priority. Their cryptic nocturnal lifestyle ma…
bacpipe: a Python package to make bioacoustic deep learning models accessible
Vincent S. Kather, Sylvain Haupert, Burooj Ghani +1
1. 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…
Linear probing enables Ship-Radiated Noise recognition with pretrained audio embeddings
Hilde I. Hummel, Sandjai Bhulai, Rob D. van der Mei +1
Even though the ocean covers the majority of the planet's surface, it remains the least explored ecosystem. As light and radio waves do not propagate through water, underwater acou…
Automated data curation for self-supervised learning in underwater acoustic analysis
Hilde I Hummel, Sandjai Bhulai, Burooj Ghani +1
The sustainability of the ocean ecosystem is threatened by increased levels of sound pollution, making monitoring crucial to understand its variability and impact. Passive acoustic…
Clustering and novel class recognition: evaluating bioacoustic deep learning feature extractors
Vincent S. Kather, Burooj Ghani, Dan Stowell
In computational bioacoustics, deep learning models are composed of feature extractors and classifiers. The feature extractors generate vector representations of the input sound se…
InsectSet459: an open dataset of insect sounds for bioacoustic machine learning
Marius Faiß, Burooj Ghani, Dan Stowell
Automatic recognition of insect sound could help us understand changing biodiversity trends around the world -- but insect sounds are challenging to recognize even for deep learnin…
Generalization in birdsong classification: impact of transfer learning methods and dataset characteristics
Burooj Ghani, Vincent J. Kalkman, Bob Planqué +3
Animal sounds can be recognised automatically by machine learning, and this has an important role to play in biodiversity monitoring. Yet despite increasingly impressive capabiliti…
Mind the Domain Gap: a Systematic Analysis on Bioacoustic Sound Event Detection
Jinhua Liang, Ines Nolasco, Burooj Ghani +3
Detecting the presence of animal vocalisations in nature is essential to study animal populations and their behaviors. A recent development in the field is the introduction of the…
Efficient speech detection in environmental audio using acoustic recognition and knowledge distillation
Drew Priebe, Burooj Ghani, Dan Stowell
The ongoing biodiversity crisis, driven by factors such as land-use change and global warming, emphasizes the need for effective ecological monitoring methods. Acoustic monitoring…
Global birdsong embeddings enable superior transfer learning for bioacoustic classification
Burooj Ghani, Tom Denton, Stefan Kahl +1
Automated bioacoustic analysis aids understanding and protection of both marine and terrestrial animals and their habitats across extensive spatiotemporal scales, and typically inv…
Few-shot bioacoustic event detection at the DCASE 2023 challenge
Ines Nolasco, Burooj Ghani, Shubhr Singh +12
Few-shot bioacoustic event detection consists in detecting sound events of specified types, in varying soundscapes, while having access to only a few examples of the class of inter…
Learning to detect an animal sound from five examples
Inês Nolasco, Shubhr Singh, Veronica Morfi +14
Automatic detection and classification of animal sounds has many applications in biodiversity monitoring and animal behaviour. In the past twenty years, the volume of digitised wil…