2018
Improving Semi-Supervised Classification for Low-Resource Speech Interaction Applications
ICASSP 2018accepted
We propose a semi-supervised learning method to improve classification performance in scenarios with limited labeled data. We employ adaptation strategies such as entropy-filtering and self-training, and show that our method achieves up to 17.2% relative improvement in UAR for a multi-class problem.…