2023
Semi-Supervised Learning with Per-Class Adaptive Confidence Scores for Acoustic Environment Classification with Imbalanced Data
Luan Vinícius Fiorio, Boris Karanov, Johan David, Wim J. van Houtum, Frans Widdershoven, Ronald M. Aarts
ICASSP 2023accepted
In this paper, we concentrate on the per-class accuracy of neural network-based classification in the context of identifying acoustic environments. Even a fully supervised learning framework with an equal amount of data for each class can lead to significant differences in class accuracies. This is…