3 citations · 3 across the 3 of their papers we have counts for
6 papers
BEANS-Next and ROOTS: Broadening Audio-Language Capabilities for Bioacoustics
Christos Plachouras, David Robinson, Marius Miron +17
Bioacoustics and ethology encompass a wide range of audio understanding tasks, many of which stand to benefit from recent advances in large audio-language models. However, progress…
Audio-to-Image Bird Species Retrieval without Audio-Image Pairs via Text Distillation
Ilyass Moummad, Marius Miron, Lukas Rauch +5
Audio-to-image retrieval offers an interpretable alternative to audio-only classification for bioacoustic species recognition, but learning aligned audio-image representations is c…
BAT: Better Audio Transformer Guided by Convex Gated Probing
Houtan Ghaffari, Lukas Rauch, Christoph Scholz +1
Probing is widely adopted in computer vision to faithfully evaluate self-supervised learning (SSL) embeddings, as finetuning may misrepresent their inherent quality. In contrast, a…
Uncertainty Calibration of Multi-Label Bird Sound Classifiers
Raphael Schwinger, Ben McEwen, Vincent S. Kather +3
Passive acoustic monitoring enables large-scale biodiversity assessment, but reliable classification of bioacoustic sounds requires not only high accuracy but also well-calibrated…
Foundation Models for Bioacoustics -- a Comparative Review
Raphael Schwinger, Paria Vali Zadeh, Lukas Rauch +4
Automated bioacoustic analysis is essential for biodiversity monitoring and conservation, requiring advanced deep learning models that can adapt to diverse bioacoustic tasks. This…
AudioProtoPNet: An interpretable deep learning model for bird sound classification
René Heinrich, Lukas Rauch, Bernhard Sick +1
Deep learning models have significantly advanced acoustic bird monitoring by being able to recognize numerous bird species based on their vocalizations. However, traditional deep l…