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Training and testing SELD systems requires datasets of diverse sound events occurring under realistic acoustic conditions. Title = "A Dataset of Reverberant Spatial Sound Scenes with Moving Sources for Sound Event Localization and Detection",īooktitle = "Proceedings of the Detection and Classification of Acoustic Scenes and Events 2020 Workshop (DCASE2020)",Ībstract = "This report details the dataset and the evaluation setup of the Sound Event Localization \\& Detection (SELD) task for the DCASE 2020 Challenge. The data collection received funding from the European Research Council, grant agreement 637422 EVERYSOUND.Ī detailed description of the dataset collection and generation, along with details on the baseline and evaluation can be found in the following = "Politis, Archontis and Adavanne, Sharath and Virtanen, Tuomas", The older measurements from five rooms were also used for the earlier development and evaluation datasets TAU Spatial Sound Events 2019, while ten additional rooms were added for this dataset. The RIRs were collected in Finland by staff of Tampere University between 12/2017 - 06/2018, and between 11/2019 - 1/2020. These recordings serve as the development dataset for the DCASE 2020 Sound Event Localization and Detection Task of the DCASE 2020 Challenge. The isolated sound event recordings used for the synthesis of the sound scenes are obtained from the NIGENS general sound events database. Each sound event in the sound scene is associated with a trajectory of its direction-of-arrival (DoA) to the recording point, and a temporal onset and offset time.
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The sound events are spatialized as either stationary sound sources in the room, or moving sound sources, in which case time-variant RIRs are used. Furthermore, each scene recording is delivered in two spatial recording formats, a microphone array one ( MIC), and first-order Ambisonics one ( FOA). The spatialization of all sound events is based on filtering through real spatial room impulse responses (RIRs), captured in multiple rooms of various shapes, sizes, and acoustical absorption properties. The TAU-NIGENS Spatial Sound Events 2020 dataset contains multiple spatial sound-scene recordings, consisting of sound events of distinct categories integrated into a variety of acoustical spaces, and from multiple source directions and distances as seen from the recording position.
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Figure 1: Overview of sound event localization and detection system.