Description and Discussion on DCASE 2026 Challenge Task 4: Spatial Semantic Segmentation of Sound Scenes
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2026
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| author | Nguyen, Binh Thien Yasuda, Masahiro Harada, Noboru Serizel, Romain Mishra, Mayank Delcroix, Marc Hernandez-Olivan, Carlos Araki, Shoko Takeuchi, Daiki Nakatani, Tomohiro Ono, Nobutaka |
| author_facet | Nguyen, Binh Thien Yasuda, Masahiro Harada, Noboru Serizel, Romain Mishra, Mayank Delcroix, Marc Hernandez-Olivan, Carlos Araki, Shoko Takeuchi, Daiki Nakatani, Tomohiro Ono, Nobutaka |
| contents | This paper presents an overview of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2026 Challenge Task 4, Spatial Semantic Segmentation of Sound Scenes (S5). The S5 task focuses on the joint detection and separation of sound events in complex spatial audio mixtures, contributing to the foundation of immersive communication. First introduced in DCASE 2025, the S5 task continues in DCASE 2026 Task 4 with key changes to better reflect real-world conditions, including allowing mixtures to contain multiple sources of the same class and to contain no target sources. In this paper, we describe task setting, along with the corresponding updates to the evaluation metrics and dataset. The experimental results of the submitted systems are also reported and analyzed. The official access point for data and code is https://github.com/nttcslab/dcase2026_task4_baseline. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2604_00776 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Description and Discussion on DCASE 2026 Challenge Task 4: Spatial Semantic Segmentation of Sound Scenes Nguyen, Binh Thien Yasuda, Masahiro Harada, Noboru Serizel, Romain Mishra, Mayank Delcroix, Marc Hernandez-Olivan, Carlos Araki, Shoko Takeuchi, Daiki Nakatani, Tomohiro Ono, Nobutaka Audio and Speech Processing This paper presents an overview of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2026 Challenge Task 4, Spatial Semantic Segmentation of Sound Scenes (S5). The S5 task focuses on the joint detection and separation of sound events in complex spatial audio mixtures, contributing to the foundation of immersive communication. First introduced in DCASE 2025, the S5 task continues in DCASE 2026 Task 4 with key changes to better reflect real-world conditions, including allowing mixtures to contain multiple sources of the same class and to contain no target sources. In this paper, we describe task setting, along with the corresponding updates to the evaluation metrics and dataset. The experimental results of the submitted systems are also reported and analyzed. The official access point for data and code is https://github.com/nttcslab/dcase2026_task4_baseline. |
| title | Description and Discussion on DCASE 2026 Challenge Task 4: Spatial Semantic Segmentation of Sound Scenes |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2604.00776 |