3 citations · 5 across the 8 of their papers we have counts for
3 papers · 1 filter
Sampling Bias Compensation for Robust Evaluation of Audio Classification Systems with Partially Labeled Evaluation Datasets
Javier Naranjo-Alcazar, Annamaria Mesaros, Tuomas Virtanen +1
The performance of acoustic machine learning systems is commonly evaluated using fully annotated test sets. In real-world deployments, however, exhaustively labeling large volumes…
Evaluating the Temporal Detection Capability of Integrated Gradients Applied on Sound Classifier
Martynas Dumpis, Tuomas Virtanen
Gradient-based attribution methods can highlight input regions important for neural network predictions, but their effectiveness for temporal sound event detection in audio classif…
Automatic Contextual Audio Denoising
Diep Luong, Konstantinos Drossos, Mikko Heikkinen +1
Audio context determines which sound components and sources are relevant and which can be perceived as irrelevant (noise) by listeners. For example, traffic noise is informative in…