{"url":"/sota/sound-event-localization-and-detection-on-1","task":{"name":"Sound Event Localization and Detection","url":"/task/sound-event-localization-and-detection","note":null},"dataset":{"name":"STARSS22","url":"/dataset/starss22"},"category":"Audio","categories":["Audio"],"category_note":null,"description":"Given multichannel audio input, a sound event detection and localization (SELD) system outputs a temporal activation track for each of the target sound classes, along with one or more corresponding spatial trajectories when the track indicates activity. This results in a spatio-temporal characterization of the acoustic scene that can be used in a wide range of machine cognition tasks, such as inference on the type of environment, self-localization, navigation without visual input or with occluded targets, tracking of specific types of sound sources, smart-home applications, scene visualization systems, and audio surveillance, among others.","description_from":"task","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","rank":"the archive's row order at snapshot; not re-ranked","rows_end_at":"2025-07-28","rows_withheld_as_spam":0,"metric_values":"the archive's strings, untouched"},"metrics":["Class-dependent localization error","Class-dependent localization recall","location-dependent F1-score (macro)","location-dependent F1-score (micro)","Localization-dependent error rate (20°)"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"Class-dependent localization error":"lower","Class-dependent localization recall":"higher","location-dependent F1-score (macro)":"higher","location-dependent F1-score (micro)":"higher","Localization-dependent error rate (20°)":"lower"}},"counts":{"rows":2,"rows_with_code":2,"rows_with_paper_page":2,"rows_dated":2,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"Baseline (FOA)","metrics":{"Class-dependent localization error":"29.3","Class-dependent localization recall":"46","Localization-dependent error rate (20°)":"71","location-dependent F1-score (macro)":"21","location-dependent F1-score (micro)":"0.36"},"uses_additional_data":false,"paper_date":"2022-06-04","paper":"/paper/starss22-a-dataset-of-spatial-recordings-of","paper_url":"https://arxiv.org/abs/2206.01948v2","paper_title":"STARSS22: A dataset of spatial recordings of real scenes with spatiotemporal annotations of sound events","code":"https://github.com/sharathadavanne/seld-dcase2022","n_code_links":2,"syntology":null},{"rank_in_archive_order":2,"model":"Baseline (MIC)","metrics":{"Class-dependent localization error":"32.2","Class-dependent localization recall":"47","location-dependent F1-score (macro)":"18","location-dependent F1-score (micro)":"0.36"},"uses_additional_data":false,"paper_date":"2022-06-04","paper":"/paper/starss22-a-dataset-of-spatial-recordings-of","paper_url":"https://arxiv.org/abs/2206.01948v2","paper_title":"STARSS22: A dataset of spatial recordings of real scenes with spatiotemporal annotations of sound events","code":"https://github.com/sharathadavanne/seld-dcase2022","n_code_links":2,"syntology":null}],"since_archive":{"claim":"Results that newer papers report for their own method, placed here by Syntology. A model pointed at the cell in the paper's own table; the number was read from that cell and checked against this leaderboard's metric, dataset, split and scale; an independent check that saw this leaderboard's other rows and every other leaderboard on the same dataset accepted it. Not reviewed by the paper's authors or by the archive's editors, and not ranked against the archive rows.","extraction_file_present":true,"measurement":{"test_papers":883,"papers_with_output":881,"judged_true":108,"judged":110,"wilson95_lower":0.9361,"measured_on":"2026-09-24","frozen_commit":"0e3de0df94"},"measurement_note":"blind adjudication of accepted entries on a held-out split of archive papers, rules frozen before the test","coverage":{"sentence":"Syntology has checked 6,885 of the 9,623 papers on this site that are newer than the archive; results from the others appear after they are checked.","complete":false,"papers_newer_than_archive":9623,"papers_checked":6885,"papers_extracted_not_yet_verified":0,"boards_without_verdict":2,"papers_not_yet_extracted":2737},"order":"newest first by month (arXiv date, else the arXiv-id month), then arXiv id descending","columns":[],"entries":[]},"syntology":{"read_at":"2026-09-25T09:33:49+00:00","claim":"Per row: N of M harvested code samples from that row's paper executed on a synthesized fixture; the other M-N are unverified. Not a reproduction of the row's number; not a correctness claim. n_pointer_only_licence counts samples the site points at rather than redistributes (a licence axis, independent of ran/unverified).","rows_with_graph_line":0,"rows_with_any_sample_ran":0,"distinct_papers_with_graph_line":0,"distinct_papers_with_any_sample_ran":0,"samples_over_distinct_papers":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"row-weighted: a paper behind several rows is counted once per row; inflated relative to samples_over_distinct_papers by design, kept for readers summing the per-row syntology blocks"}}}