Multitask frame-level learning for few-shot sound event detection

arXiv:2403.11091v1 Announce Type: cross
Abstract: This paper focuses on few-shot Sound Event Detection (SED), which aims to automatically recognize and classify sound events with limited samples. However, prevailing methods methods in few-shot SED predominantly rely on segment-level predictions, which often providing detailed, fine-grained predictions, particularly for events of brief duration. Although frame-level prediction strategies have been proposed to overcome these limitations, these strategies commonly face difficulties with prediction truncation caused by background noise. To alleviate this issue, we introduces an …

abstract arxiv cs.cv cs.sd detection eess.as event events few-shot fine-grained however paper predictions samples segment sound type