Fsd50k: an open dataset of human-labeled sound events
Most existing datasets for sound event recognition (SER) are relatively small and/or domain-
specific, with the exception of AudioSet, based on over 2 M tracks from YouTube videos and …
specific, with the exception of AudioSet, based on over 2 M tracks from YouTube videos and …
A systematic literature review on the use of deep learning in precision livestock detection and localization using unmanned aerial vehicles
DBM Yousefi, ASM Rafie, SAR Al-Haddad… - Ieee …, 2022 - ieeexplore.ieee.org
With the ever-increasing importance of dairy and meat production, precision livestock
farming (PLF) using advanced information technologies is emerging to improve farming …
farming (PLF) using advanced information technologies is emerging to improve farming …
Psla: Improving audio tagging with pretraining, sampling, labeling, and aggregation
Audio tagging is an active research area and has a wide range of applications. Since the
release of AudioSet, great progress has been made in advancing model performance, which …
release of AudioSet, great progress has been made in advancing model performance, which …
Sound event detection in domestic environments with weakly labeled data and soundscape synthesis
This paper presents Task 4 of the Detection and Classification of Acoustic Scenes and
Events (DCASE) 2019 challenge and provides a first analysis of the challenge results. The …
Events (DCASE) 2019 challenge and provides a first analysis of the challenge results. The …
A comparison of five multiple instance learning pooling functions for sound event detection with weak labeling
Sound event detection (SED) entails two subtasks: recognizing what types of sound events
are present in an audio stream (audio tagging), and pinpointing their onset and offset times …
are present in an audio stream (audio tagging), and pinpointing their onset and offset times …
Learning sound event classifiers from web audio with noisy labels
As sound event classification moves towards larger datasets, issues of label noise become
inevitable. Web sites can supply large volumes of user-contributed audio and metadata, but …
inevitable. Web sites can supply large volumes of user-contributed audio and metadata, but …
Weakly-supervised audio-visual segmentation
S Mo, B Raj - Advances in Neural Information Processing …, 2024 - proceedings.neurips.cc
Audio-visual segmentation is a challenging task that aims to predict pixel-level masks for
sound sources in a video. Previous work applied a comprehensive manually designed …
sound sources in a video. Previous work applied a comprehensive manually designed …
Training sound event detection on a heterogeneous dataset
N Turpault, R Serizel - arXiv preprint arXiv:2007.03931, 2020 - arxiv.org
Training a sound event detection algorithm on a heterogeneous dataset including both
recorded and synthetic soundscapes that can have various labeling granularity is a non …
recorded and synthetic soundscapes that can have various labeling granularity is a non …
Threshold independent evaluation of sound event detection scores
J Ebbers, R Haeb-Umbach… - ICASSP 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
Performing an adequate evaluation of sound event detection (SED) systems is far from trivial
and is still subject to ongoing research. The recently proposed polyphonic sound detection …
and is still subject to ongoing research. The recently proposed polyphonic sound detection …
Cmkd: Cnn/transformer-based cross-model knowledge distillation for audio classification
Audio classification is an active research area with a wide range of applications. Over the
past decade, convolutional neural networks (CNNs) have been the de-facto standard …
past decade, convolutional neural networks (CNNs) have been the de-facto standard …