5 citations · 5 across the 4 of their papers we have counts for
5 papers
LHGNN: Local-Higher Order Graph Neural Networks For Audio Classification and Tagging
Shubhr Singh, Emmanouil Benetos, Huy Phan +1
Transformers have set new benchmarks in audio processing tasks, leveraging self-attention mechanisms to capture complex patterns and dependencies within audio data. However, their…
Acoustic identification of individual animals with hierarchical contrastive learning
Ines Nolasco, Ilyass Moummad, Dan Stowell +1
Acoustic identification of individual animals (AIID) is closely related to audio-based species classification but requires a finer level of detail to distinguish between individual…
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…
ATGNN: Audio Tagging Graph Neural Network
Shubhr Singh, Christian J. Steinmetz, Emmanouil Benetos +2
Deep learning models such as CNNs and Transformers have achieved impressive performance for end-to-end audio tagging. Recent works have shown that despite stacking multiple layers,…
Few-shot bioacoustic event detection at the DCASE 2022 challenge
I. Nolasco, S. Singh, E. Vidana-Villa +12
Few-shot sound event detection is the task of detecting sound events, despite having only a few labelled examples of the class of interest. This framework is particularly useful in…