116 citations · 236 across the 15 of their papers we have counts for
3 papers · 1 filter
Improving Sound Event Classification by Increasing Shift Invariance in Convolutional Neural Networks
Eduardo Fonseca, Andres Ferraro, Xavier Serra
Recent studies have put into question the commonly assumed shift invariance property of convolutional networks, showing that small shifts in the input can affect the output predict…
The Benefit Of Temporally-Strong Labels In Audio Event Classification
Shawn Hershey, Daniel P W Ellis, Eduardo Fonseca +4
To reveal the importance of temporal precision in ground truth audio event labels, we collected precise (~0.1 sec resolution) "strong" labels for a portion of the AudioSet dataset.…
Self-Supervised Learning from Automatically Separated Sound Scenes
Eduardo Fonseca, Aren Jansen, Daniel P. W. Ellis +7
Real-world sound scenes consist of time-varying collections of sound sources, each generating characteristic sound events that are mixed together in audio recordings. The associati…