Gate‐Align‐SED: Semi‐Supervised Sound Event Detection via Adaptive Feature Gating and Cross‐Task Alignment in Situation Awareness

In complex real‐world environments such as disaster monitoring, effective sound event detection (SED) is often hindered by the presence of noise and limited labeled data. This article presents Gate‐Align‐SED, a unified semi‐supervised framework designed to bridge the gap between clip‐level and frame...

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Detalhes bibliográficos

Principais autores:	Jieli Chen, Li‐Minn Ang, Chee Shen Lim, Kah Phooi Seng, Jeremy Smith
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Wiley 2026-06-01
Colecção:	Advanced Intelligent Systems
Assuntos:	disaster monitoring representation learning semi‐supervised learning situation awareness sound event detection
Acesso em linha:	https://doi.org/10.1002/aisy.70355
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