Large-Scale Weakly Labeled Semi-Supervised Sound Event Detection in Domestic Environments
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Abstract (arXiv)
This paper presents DCASE 2018 task 4. The task evaluates systems for the large-scale detection of sound events using weakly labeled data (without time boundaries). The target of the systems is to provide not only the event class but also the event time boundaries given that multiple events can be present in an audio recording. Another challenge of the task is to explore the possibility to exploit a large amount of unbalanced and unlabeled training data together with a small weakly labeled training set to improve system performance. The data are Youtube video excerpts from domestic context which have many applications such as ambient assisted living. The domain was chosen due to the scientific challenges (wide variety of sounds, time-localized events.. .) and potential industrial applications .
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jul 2018.
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Citing papers per year: 2021: 4; 2022: 2; 2023: 0; 2024: 1; 2025: 1; 2026: 2.
10 papers.
- 2021Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detectioncited by 7
- 2022Reliable Decision from Multiple Subtasks through Threshold Optimization: Content Moderation in the Wildcited by 7
- 2024Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shiftcited by 7
- 2021The impact of non-target events in synthetic soundscapes for sound event detectioncited by 4
- 2021Fast threshold optimization for multi-label audio tagging using Surrogate gradient learningcited by 2
- 2022A benchmark of state-of-the-art sound event detection systems evaluated on synthetic soundscapescited by 1
- 2021Peer Collaborative Learning for Polyphonic Sound Event Detectioncited by 0
- 2025Formula-Supervised Sound Event Detection: Pre-Training Without Real Datacited by 0
- 2026Auto-AEG: Scalable Data Construction for Open-Vocabulary Audio Event Groundingcited by 0
- 2026MAST: Label-Efficient, Robust, and Generalizable Sound Detection for Biodiversity Monitoring via Masked Audio Pretraining and Self-Trainingcited by 0
- 2026MAST: Label-Efficient, Robust, and Generalizable Sound Detection for Biodiversity Monitoring via Masked Audio Pretraining and Self-Training14 Sep 2026
- 2026Auto-AEG: Scalable Data Construction for Open-Vocabulary Audio Event Grounding5 Jul 2026
- 2025Formula-Supervised Sound Event Detection: Pre-Training Without Real Data6 Apr 2025
- 2024Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift5 Feb 2024
- 2022Reliable Decision from Multiple Subtasks through Threshold Optimization: Content Moderation in the Wild16 Aug 2022
- 2022A benchmark of state-of-the-art sound event detection systems evaluated on synthetic soundscapes3 Feb 2022
- 2021Peer Collaborative Learning for Polyphonic Sound Event Detection7 Oct 2021
- 2021Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detection5 Oct 2021
- 2021The impact of non-target events in synthetic soundscapes for sound event detection28 Sep 2021
- 2021Fast threshold optimization for multi-label audio tagging using Surrogate gradient learning1 Mar 2021