Online Active Learning For Sound Event Detection
Published in arXiv preprint arXiv:2309.14460, 2023
We propose an online active learning framework for sound event detection that efficiently selects the most informative samples for annotation. Our approach enables continuous model improvement with minimal human labeling effort by identifying uncertain or novel audio segments in streaming data. The method is designed for practical deployment scenarios where labeled data is scarce and annotation resources are limited.
Recommended citation: @article{lindsey2023online, title={Online Active Learning For Sound Event Detection}, author={Lindsey, Mark and Shah, Ankit and Kubala, Francis and Stern, Richard M}, journal={arXiv preprint arXiv:2309.14460}, year={2023} }
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