{"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/is-neural-machine-translation-ready-for","title":"Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions","arxiv_id":"1610.01108","date":"2016-10-04","proceeding":"IWSLT 2016 12","authors":["Marcin Junczys-Dowmunt","Tomasz Dwojak","Hieu Hoang"],"abstract":"In this paper we provide the largest published comparison of translation\nquality for phrase-based SMT and neural machine translation across 30\ntranslation directions. For ten directions we also include hierarchical\nphrase-based MT. Experiments are performed for the recently published United\nNations Parallel Corpus v1.0 and its large six-way sentence-aligned subcorpus.\nIn the second part of the paper we investigate aspects of translation speed,\nintroducing AmuNMT, our efficient neural machine translation decoder. We\ndemonstrate that current neural machine translation could already be used for\nin-production systems when comparing words-per-second ratios.","url_abs":"http://arxiv.org/abs/1610.01108v3","url_pdf":"http://arxiv.org/pdf/1610.01108v3.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":"is-neural-machine-translation-ready-for","repo_url":"https://github.com/lkfo415579/amun","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"is-neural-machine-translation-ready-for","repo_url":"https://github.com/marian-nmt/amun","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1610.01108","atlas_url":"https://app.syntology.ai/?focus=1610.01108","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}