{"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/ap18-olr-challenge-three-tasks-and-their","title":"AP18-OLR Challenge: Three Tasks and Their Baselines","arxiv_id":"1806.00616","date":"2018-06-02","proceeding":null,"authors":["Zhiyuan Tang","Dong Wang","Qing Chen"],"abstract":"The third oriental language recognition (OLR) challenge AP18-OLR is\nintroduced in this paper, including the data profile, the tasks and the\nevaluation principles. Following the events in the last two years, namely\nAP16-OLR and AP17-OLR, the challenge this year focuses on more challenging\ntasks, including (1) short-duration utterances, (2) confusing languages, and\n(3) open-set recognition. The same as the previous events, the data of AP18-OLR\nis also provided by SpeechOcean and the NSFC M2ASR project. Baselines based on\nboth the i-vector model and neural networks are constructed for the\nparticipants' reference. We report the baseline results on the three tasks and\ndemonstrate that the three tasks are truly challenging. All the data is free\nfor participants, and the Kaldi recipes for the baselines have been published\nonline.","url_abs":"http://arxiv.org/abs/1806.00616v1","url_pdf":"http://arxiv.org/pdf/1806.00616v1.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":"ap18-olr-challenge-three-tasks-and-their","repo_url":"https://github.com/Rithmax/Sub-band-Envelope-Features-Using-Frequency-Domain-Linear-Prediction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"open-set-learning","task_name":"Open Set Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}