Sound Event Detection and Separation: a Benchmark on Desed Synthetic Soundscapes
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Abstract (arXiv)
We propose a benchmark of state-of-the-art sound event detection systems (SED). We designed synthetic evaluation sets to focus on specific sound event detection challenges. We analyze the performance of the submissions to DCASE 2021 task 4 depending on time related modifications (time position of an event and length of clips) and we study the impact of non-target sound events and reverberation. We show that the localization in time of sound events is still a problem for SED systems. We also show that reverberation and non-target sound events are severely degrading the performance of the SED systems. In the latter case, sound separation seems like a promising solution.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Nov 2020.
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Citing papers per year: 2021: 4; 2022: 1; 2023: 0; 2024: 2; 2025: 0; 2026: 2.
9 papers.
- 2021You Only Hear Once: A YOLO-like Algorithm for Audio Segmentation and Sound Event Detectioncited by 10
- 2021Self-Supervised Learning from Automatically Separated Sound Scenescited by 6
- 2024Real-time Low-latency Music Source Separation using Hybrid Spectrogram-TasNetcited by 3
- 2021Self-training with noisy student model and semi-supervised loss function for dcase 2021 challenge task 4cited by 2
- 2026SpurAudio: A Benchmark for Studying Shortcut Learning in Few-Shot Audio Classificationcited by 2
- 2021Couple Learning for semi-supervised sound event detectioncited by 1
- 2022A benchmark of state-of-the-art sound event detection systems evaluated on synthetic soundscapescited by 1
- 2024Improving snore detection under limited dataset through harmonic/percussive source separation and convolutional neural networkscited by 0
- 2026REVE: Efficient Hallucination Correction for Large Audio-Language Models via Reused Encoder Statescited by 0
- 2026REVE: Efficient Hallucination Correction for Large Audio-Language Models via Reused Encoder States22 Sep 2026
- 2026SpurAudio: A Benchmark for Studying Shortcut Learning in Few-Shot Audio Classification13 May 2026
- 2024Improving snore detection under limited dataset through harmonic/percussive source separation and convolutional neural networks31 Oct 2024
- 2024Real-time Low-latency Music Source Separation using Hybrid Spectrogram-TasNet27 Feb 2024
- 2022A benchmark of state-of-the-art sound event detection systems evaluated on synthetic soundscapes3 Feb 2022
- 2021Couple Learning for semi-supervised sound event detection12 Oct 2021
- 2021You Only Hear Once: A YOLO-like Algorithm for Audio Segmentation and Sound Event Detection1 Sep 2021
- 2021Self-training with noisy student model and semi-supervised loss function for dcase 2021 challenge task 46 Jul 2021
- 2021Self-Supervised Learning from Automatically Separated Sound Scenes5 May 2021