Active Learning for Sound Event Classification by Clustering Unlabeled Data

@inproceedings{Tuomas2017ActiveLF,
  title={Active Learning for Sound Event Classification by Clustering Unlabeled Data},
  author={Zhao Shuyang Toni Heittola Tuomas},
  year={2017}
}
  • Zhao Shuyang Toni Heittola Tuomas
  • Published 2017
This paper proposes a novel active learning method to save annotation effort when preparing material to train sound event classifiers. K-medoids clustering is performed on unlabeled sound segments, and medoids of clusters are presented to annotators for labeling. The annotated label for a medoid is used to derive predicted labels for other cluster members. The obtained labels are used to build a classifier using supervised training. The accuracy of the resulted classifier is used to evaluate… CONTINUE READING