mlsanityData to 7 Oct 2026

The impact of non-target events in synthetic soundscapes for sound event detection

arXiv 2109.14061 ↗First posted 28 Sep 2021eess.AS cs.LG cs.SDcited by 4

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Abstract (arXiv)

Detection and Classification Acoustic Scene and Events Challenge 2021 Task 4 uses a heterogeneous dataset that includes both recorded and synthetic soundscapes. Until recently only target sound events were considered when synthesizing the soundscapes. However, recorded soundscapes often contain a substantial amount of non-target events that may affect the performance. In this paper, we focus on the impact of these non-target events in the synthetic soundscapes. Firstly, we investigate to what extent using non-target events alternatively during the training or validation phase (or none of them) helps the system to correctly detect target events. Secondly, we analyze to what extend adjusting the signal-to-noise ratio between target and non-target events at training improves the sound event detection performance. The results show that using both target and non-target events for only one of the phases (validation or training) helps the system to properly detect sound events, outperforming the baseline (which uses non-target events in both phases). The paper also reports the results of a preliminary study on evaluating the system on clips that contain only non-target events. This opens questions for future work on non-target subset and acoustic similarity between target and non-target events which might confuse the system.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 8 of its 21 references that are in the map. First posted on arXiv 28 Sep 2021.

Builds on

8 of 21 references.

References · 8

  1. 2020FSD50K: An Open Dataset of Human-Labeled Sound Eventscited by 339
  2. 2021The Benefit Of Temporally-Strong Labels In Audio Event Classificationcited by 83
  3. 2019A Framework for the Robust Evaluation of Sound Event Detectioncited by 28
  4. 2020What's All the FUSS About Free Universal Sound Separation Data?cited by 22
  5. 2018Adaptive pooling operators for weakly labeled sound event detectioncited by 21
  6. 2018A Closer Look at Weak Label Learning for Audio Eventscited by 11
  7. 2018Large-Scale Weakly Labeled Semi-Supervised Sound Event Detection in Domestic Environmentscited by 10
  8. 2018SONYC: A System for the Monitoring, Analysis and Mitigation of Urban Noise Pollutioncited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1; 2026: 1.

4 papers.