Machine learning from training data with a skewed distribution of exampl...
The aim of the Detection and Classification of Acoustic Scenes and Event...
Music tagging and content-based retrieval systems have traditionally bee...
To reveal the importance of temporal precision in ground truth audio eve...
Real-world sound scenes consist of time-varying collections of sound sou...
Recent progress in deep learning has enabled many advances in sound
sepa...
The study of label noise in sound event recognition has recently gained
...
Deep learning approaches have recently achieved impressive performance o...
Humans do not acquire perceptual abilities in the way we train machines....
This paper introduces Task 2 of the DCASE2019 Challenge, titled "Audio
t...
As sound event classification moves towards larger datasets, issues of l...
Speech activity detection (or endpointing) is an important processing st...
This paper describes Task 2 of the DCASE 2018 Challenge, titled
"General...
Even in the absence of any explicit semantic annotation, vast collection...
Convolutional Neural Networks (CNNs) have proven very effective in image...
We propose a simplified model of attention which is applicable to
feed-f...