Who Calls The Shots? Rethinking Few-Shot Learning for Audio

@article{Wang2021WhoCT,
  title={Who Calls The Shots? Rethinking Few-Shot Learning for Audio},
  author={Yu Wang and Nicholas J. Bryan and Justin Salamon and M. Cartwright and Juan Pablo Bello},
  journal={2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)},
  year={2021},
  pages={36-40}
}
  • Yu WangNicholas J. Bryan J. Bello
  • Published 17 October 2021
  • Computer Science
  • 2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)
Few-shot learning aims to train models that can recognize novel classes given just a handful of labeled examples, known as the support set. While the field has seen notable advances in recent years, they have often focused on multi-class image classification. Audio, in contrast, is often multi-label due to overlapping sounds, resulting in unique properties such as polyphony and signal-to-noise ratios (SNR). This leads to unanswered questions concerning the impact such audio properties may have… 

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