{"url":"/sota/speaker-diarization-on-etape","task":{"name":"Speaker Diarization","url":"/task/speaker-diarization","note":null},"dataset":{"name":"ETAPE","url":null},"category":"Speech","categories":["Speech"],"category_note":null,"description":"**Speaker Diarization** is the task of segmenting and co-indexing audio recordings by speaker. The way the task is commonly defined, the goal is not to identify known speakers, but to co-index segments that are attributed to the same speaker; in other words, diarization implies finding speaker boundaries and grouping segments that belong to the same speaker, and, as a by-product, determining the number of distinct speakers. In combination with speech recognition, diarization enables speaker-attributed speech-to-text transcription.\n\n\n<span class=\"description-source\">Source: [Improving Diarization Robustness using Diversification, Randomization and the DOVER Algorithm ](https://arxiv.org/abs/1910.11691)</span>","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":["DER(%)","FA","Miss"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"DER(%)":null,"FA":null,"Miss":null}},"counts":{"rows":3,"rows_with_code":3,"rows_with_paper_page":3,"rows_dated":3,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"pyannote (waveform)","metrics":{"DER(%)":"4.9","FA":"4.2","Miss":"0.7"},"uses_additional_data":false,"paper_date":"2019-11-04","paper":"/paper/pyannoteaudio-neural-building-blocks-for","paper_url":"https://arxiv.org/abs/1911.01255v1","paper_title":"pyannote.audio: neural building blocks for speaker diarization","code":"https://github.com/pyannote/pyannote-audio","n_code_links":3,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":0}},{"rank_in_archive_order":2,"model":"pyannote (MFCC)","metrics":{"DER(%)":"5.6","FA":"5.2","Miss":"0.4"},"uses_additional_data":false,"paper_date":"2019-11-04","paper":"/paper/pyannoteaudio-neural-building-blocks-for","paper_url":"https://arxiv.org/abs/1911.01255v1","paper_title":"pyannote.audio: neural building blocks for speaker diarization","code":"https://github.com/pyannote/pyannote-audio","n_code_links":3,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":0}},{"rank_in_archive_order":3,"model":"Baseline","metrics":{"DER(%)":"7.7","FA":"7.5","Miss":"0.2"},"uses_additional_data":false,"paper_date":"2019-11-04","paper":"/paper/pyannoteaudio-neural-building-blocks-for","paper_url":"https://arxiv.org/abs/1911.01255v1","paper_title":"pyannote.audio: neural building blocks for speaker diarization","code":"https://github.com/pyannote/pyannote-audio","n_code_links":3,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":0}}],"since_archive":{"present":false,"note":"No Syntology-extracted rows are published in this build."},"syntology":{"read_at":"2026-09-24T18:15:14+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":3,"rows_with_any_sample_ran":3,"distinct_papers_with_graph_line":1,"distinct_papers_with_any_sample_ran":1,"samples_over_distinct_papers":{"n_ran":1,"n_unverified":0,"n_samples":1,"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":3,"n_unverified":0,"n_samples":3,"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"}}}