{"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/word-and-phrase-translation-with-word2vec","title":"Word and Phrase Translation with word2vec","arxiv_id":"1705.03127","date":"2017-05-09","proceeding":null,"authors":["Stefan Jansen"],"abstract":"Word and phrase tables are key inputs to machine translations, but costly to\nproduce. New unsupervised learning methods represent words and phrases in a\nhigh-dimensional vector space, and these monolingual embeddings have been shown\nto encode syntactic and semantic relationships between language elements. The\ninformation captured by these embeddings can be exploited for bilingual\ntranslation by learning a transformation matrix that allows matching relative\npositions across two monolingual vector spaces. This method aims to identify\nhigh-quality candidates for word and phrase translation more cost-effectively\nfrom unlabeled data.\n  This paper expands the scope of previous attempts of bilingual translation to\nfour languages (English, German, Spanish, and French). It shows how to process\nthe source data, train a neural network to learn the high-dimensional\nembeddings for individual languages and expands the framework for testing their\nquality beyond the English language. Furthermore, it shows how to learn\nbilingual transformation matrices and obtain candidates for word and phrase\ntranslation, and assess their quality.","url_abs":"http://arxiv.org/abs/1705.03127v4","url_pdf":"http://arxiv.org/pdf/1705.03127v4.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":"word-and-phrase-translation-with-word2vec","repo_url":"https://github.com/svjan5/CNN-for-text-classification","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"translation","task_name":"Translation"}],"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}