{"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/attention-based-sequence-to-sequence-model","title":"Attention-based sequence-to-sequence model for speech recognition: development of state-of-the-art system on LibriSpeech and its application to non-native English","arxiv_id":"1810.13088","date":"2018-10-31","proceeding":null,"authors":["Yan Yin","Ramon Prieto","Bin Wang","Jianwei Zhou","Yiwei Gu","Yang Liu","Hui Lin"],"abstract":"Recent research has shown that attention-based sequence-to-sequence models\nsuch as Listen, Attend, and Spell (LAS) yield comparable results to\nstate-of-the-art ASR systems on various tasks. In this paper, we describe the\ndevelopment of such a system and demonstrate its performance on two tasks:\nfirst we achieve a new state-of-the-art word error rate of 3.43% on the test\nclean subset of LibriSpeech English data; second on non-native English speech,\nincluding both read speech and spontaneous speech, we obtain very competitive\nresults compared to a conventional system built with the most updated Kaldi\nrecipe.","url_abs":"http://arxiv.org/abs/1810.13088v2","url_pdf":"http://arxiv.org/pdf/1810.13088v2.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":"attention-based-sequence-to-sequence-model","repo_url":"https://github.com/30stomercury/Automatic_Speech_Recognition","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"speech-recognition","task_name":"Speech Recognition"},{"task_slug":"speech-recognition-1","task_name":"speech-recognition"}],"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}