{"url":"/dataset/tut-sound-events-2018","name":"TUT Sound Events 2018","full_name":"TUT Sound Events 2018","description_markdown":"The TUT Sounds Event 2018 dataset consists of real-life first order Ambisonic (FOA) format recordings with stationary point sources each associated with a spatial coordinate. The dataset was generated by collecting impulse responses (IR) from a real environment using the Eigenmike spherical microphone array. The measurement was done by slowly moving a Genelec G Two loudspeaker continuously playing a maximum length sequence around the array in circular trajectory in one elevation at a time. The playback volume was set to be 30 dB greater than the ambient sound level. The recording was done in a corridor inside the university with classrooms around it during work hours. The IRs were collected at elevations −40 to 40 with 10-degree increments at 1 m from the Eigenmike and at elevations −20 to 20 with 10-degree increments at 2 m.\n\nSource: [https://zenodo.org/record/1237793](https://zenodo.org/record/1237793)\nImage Source: [https://www.cs.tut.fi/~mesaros/pubs/mesaros_eusipco2016-dcase.pdf](https://www.cs.tut.fi/~mesaros/pubs/mesaros_eusipco2016-dcase.pdf)","description_withheld":null,"homepage":"https://zenodo.org/record/1237793","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":null,"title":"TUT Sound Events 2018 - Ambisonic, Reverberant and Real-life Impulse Response Dataset","first_author":null,"url":"https://doi.org/10.5281/zenodo.1237793"},"license":{"name":"Other (Non-Commercial)","url":"https://zenodo.org/record/1237793"},"modalities":[{"name":"Audio","url":"/datasets/modality/audio"}],"tasks":[{"name":"Acoustic Scene Classification","url":"/task/acoustic-scene-classification","datasets_with_task":"/datasets/task/acoustic-scene-classification"},{"name":"Sound Event Detection","url":"/task/sound-event-detection","datasets_with_task":"/datasets/task/sound-event-detection"},{"name":"Self-Driving Cars","url":"/task/self-driving-cars","datasets_with_task":"/datasets/task/self-driving-cars"}],"languages":[],"variants":["TUT Sound Events 2018"],"data_loaders":[],"num_papers_in_archive":0,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}