{"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/active-learning-for-interactive-neural","title":"Active Learning for Interactive Neural Machine Translation of Data Streams","arxiv_id":"1807.11243","date":"2018-07-30","proceeding":"CONLL 2018 10","authors":["Álvaro Peris","Francisco Casacuberta"],"abstract":"We study the application of active learning techniques to the translation of\nunbounded data streams via interactive neural machine translation. The main\nidea is to select, from an unbounded stream of source sentences, those worth to\nbe supervised by a human agent. The user will interactively translate those\nsamples. Once validated, these data is useful for adapting the neural machine\ntranslation model.\n  We propose two novel methods for selecting the samples to be validated. We\nexploit the information from the attention mechanism of a neural machine\ntranslation system. Our experiments show that the inclusion of active learning\ntechniques into this pipeline allows to reduce the effort required during the\nprocess, while increasing the quality of the translation system. Moreover, it\nenables to balance the human effort required for achieving a certain\ntranslation quality. Moreover, our neural system outperforms classical\napproaches by a large margin.","url_abs":"http://arxiv.org/abs/1807.11243v2","url_pdf":"http://arxiv.org/pdf/1807.11243v2.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":"active-learning-for-interactive-neural","repo_url":"https://github.com/lvapeab/nmt-keras","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"active-learning","task_name":"Active Learning"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1807.11243","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}