1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.SD2021
Comparison of semi-supervised deep learning algorithms for audio classification
Léo Cances, Etienne Labbé, Thomas Pellegrini
In this article, we adapted five recent SSL methods to the task of audio classification. The first two methods, namely Deep Co-Training (DCT) and Mean Teacher (MT), involve two col…
eess.AS2019
Evaluation of post-processing algorithms for polyphonic sound event detection
Leo Cances, Patrice Guyot, Thomas Pellegrini
Sound event detection (SED) aims at identifying audio events (audio tagging task) in recordings and then locating them temporally (localization task). This last task ends with the…
cs.SD2019★ 1 cited
Cosine-similarity penalty to discriminate sound classes in weakly-supervised sound event detection
Thomas Pellegrini, Léo Cances
The design of new methods and models when only weakly-labeled data are available is of paramount importance in order to reduce the costs of manual annotation and the considerable h…