{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/but-system-description-for-dihard-speech","title":"BUT System Description for DIHARD Speech Diarization Challenge 2019","arxiv_id":"1910.08847","date":"2019-10-19","proceeding":null,"authors":["Federico Landini","Shuai Wang","Mireia Diez","Lukáš Burget","Pavel Matějka","Kateřina Žmolíková","Ladislav Mošner","Oldřich Plchot","Ondřej Novotný","Hossein Zeinali","Johan Rohdin"],"abstract":"This paper describes the systems developed by the BUT team for the four tracks of the second DIHARD speech diarization challenge. For tracks 1 and 2 the systems were based on performing agglomerative hierarchical clustering (AHC) over x-vectors, followed by the Bayesian Hidden Markov Model (HMM) with eigenvoice priors applied at x-vector level followed by the same approach applied at frame level. For tracks 3 and 4, the systems were based on performing AHC using x-vectors extracted on all channels.","url_abs":"https://arxiv.org/abs/1910.08847v1","url_pdf":"https://arxiv.org/pdf/1910.08847v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"but-system-description-for-dihard-speech","repo_url":"https://github.com/BUTSpeechFIT/VBx","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}