• Corpus ID: 234762963

Federated Learning With Highly Imbalanced Audio Data

@article{Green2021FederatedLW,
  title={Federated Learning With Highly Imbalanced Audio Data},
  author={Marc C. Green and MarkD . Plumbley},
  journal={ArXiv},
  year={2021},
  volume={abs/2105.08550}
}
Federated learning (FL) is a privacy-preserving machine learning method that has been proposed to allow training of models using data from many different clients, without these clients having to transfer all their data to a central server. There has as yet been relatively little consideration of FL or other privacy-preserving methods in audio. In this paper, we investigate using FL for a sound event detection task using audio from the FSD50K dataset. Audio is split into clients based on… 

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