{"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/improving-the-previous-state-of-the-art","title":"Improving the previous state-of-the-art Frisian ASR by fine-tuning XLS-R","arxiv_id":null,"date":"2023-03-31","proceeding":"- 2023 3","authors":["Dragoș Alexandru Bălan","Golshid Shekoufandeh"],"abstract":"Automatic Speech Recognition (ASR), a system that converts human speech to text, has a major role in digitizing human communication. Despite their significance, most of these systems are designed for higher-resourced languages, like English, Mandarin, or Spanish, leaving lower-resourced languages, such as Frisian, underrepresented. To address this issue, our paper introduces a fine-tuned ASR model based on the Wav2Vec 2.0 XLS-R architecture, trained on the Common Voice corpus version 12.0, to transcribe Frisian speech. With a learning rate of 8e-5, our proposed ASR system has achieved a 15.99% word error rate (WER), surpassing the previous state-of-the-art of 16.25% and serving as a benchmark for future research in this field.","url_abs":"https://drive.google.com/file/d/1CAbwTxsabcRKH7UJwYJyxD1F32cjhkJb/view?usp=share_link","url_pdf":"https://drive.google.com/file/d/1CAbwTxsabcRKH7UJwYJyxD1F32cjhkJb/view?usp=share_link","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":[],"tasks":[{"task_slug":"automatic-speech-recognition-2","task_name":"Automatic Speech Recognition"},{"task_slug":"automatic-speech-recognition","task_name":"Automatic Speech Recognition (ASR)"},{"task_slug":"speech-recognition","task_name":"Speech Recognition"},{"task_slug":"speech-to-text","task_name":"Speech-to-Text"},{"task_slug":"speech-recognition-1","task_name":"speech-recognition"}],"methods":[{"method_slug":"xlsr","method_name":"XLSR"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/speech-recognition-on-common-voice-frisian","task":"Speech Recognition","dataset":"Common Voice Frisian","model":"wav2vec2-large-xls-r-1b-frisian","rank_in_archive_order":1,"of":1,"metrics":{"Test WER":"15.99%"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}