Proposal-based Few-shot Sound Event Detection for Speech and Environmental Sounds with Perceivers

Understand

Many applications involve detecting and localizing specific sound events within long, untrimmed documents, including keyword spotting, medical observation, and bioacoustic monitoring for conservation.

• Deep learning techniques often set the state-of-the-art for these tasks.
• However, for some types of events, there is insufficient labeled data to train such models.
• In this paper, we propose a region proposal-based approach to few-shot sound event detection utilizing the Perceiver architecture.