Few-Shot Emergency Siren Detection

  title={Few-Shot Emergency Siren Detection},
  author={Michela Cantarini and Leonardo Gabrielli and Stefano Squartini},
  journal={Sensors (Basel, Switzerland)},
It is a well-established practice to build a robust system for sound event detection by training supervised deep learning models on large datasets, but audio data collection and labeling are often challenging and require large amounts of effort. This paper proposes a workflow based on few-shot metric learning for emergency siren detection performed in steps: prototypical networks are trained on publicly available sources or synthetic data in multiple combinations, and at inference time, the… 

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