Federated Learning With Highly Imbalanced Audio Data
Marc C. Green,
Mark D. Plumbley
Abstract: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 uploader metadata. This… Show more
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