10 citations · 11 across the 8 of their papers we have counts for
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cs.SD2025
Joint Analysis of Acoustic Scenes and Sound Events Based on Semi-Supervised Training of Sound Events With Partial Labels
Keisuke Imoto
Annotating time boundaries of sound events is labor-intensive, limiting the scalability of strongly supervised learning in audio detection. To reduce annotation costs, weakly-super…
cs.SD2025★ 1 cited
Description and Discussion on DCASE 2025 Challenge Task 2: First-shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
Tomoya Nishida, Noboru Harada, Daisuke Niizumi +9
This paper introduces the task description for the Detection and Classification of Acoustic Scenes and Events (DCASE) 2025 Challenge Task 2, titled "First-shot unsupervised anomalo…