{"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/aishell-2-transforming-mandarin-asr-research","title":"AISHELL-2: Transforming Mandarin ASR Research Into Industrial Scale","arxiv_id":"1808.10583","date":"2018-08-31","proceeding":null,"authors":["Jiayu Du","Xingyu Na","Xuechen Liu","Hui Bu"],"abstract":"AISHELL-1 is by far the largest open-source speech corpus available for\nMandarin speech recognition research. It was released with a baseline system\ncontaining solid training and testing pipelines for Mandarin ASR. In AISHELL-2,\n1000 hours of clean read-speech data from iOS is published, which is free for\nacademic usage. On top of AISHELL-2 corpus, an improved recipe is developed and\nreleased, containing key components for industrial applications, such as\nChinese word segmentation, flexible vocabulary expension and phone set\ntransformation etc. Pipelines support various state-of-the-art techniques, such\nas time-delayed neural networks and Lattic-Free MMI objective funciton. In\naddition, we also release dev and test data from other channels(Android and\nMic). For research community, we hope that AISHELL-2 corpus can be a solid\nresource for topics like transfer learning and robust ASR. For industry, we\nhope AISHELL-2 recipe can be a helpful reference for building meaningful\nindustrial systems and products.","url_abs":"http://arxiv.org/abs/1808.10583v2","url_pdf":"http://arxiv.org/pdf/1808.10583v2.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":[],"tasks":[{"task_slug":"chinese-word-segmentation","task_name":"Chinese Word Segmentation"},{"task_slug":"speech-recognition","task_name":"Speech Recognition"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"},{"task_slug":"speech-recognition-1","task_name":"speech-recognition"}],"methods":[],"datasets_introduced":[{"slug":"aishell-2","name":"AISHELL-2","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1808.10583","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}