{"type":"ScholarlyArticle","title":"Iterative Learning of Parallel Lexicons and Phrases from Non-Parallel Corpora","authors":[{"name":"Meiping Dong","slug":"meiping-dong","given":"Meiping","family":"Dong","affiliation":""},{"name":"Yang Liu","slug":"yang-liu-3","given":"Yang","family":"Liu","affiliation":""},{"name":"Huan-Bo Luan","slug":"huan-bo-luan","given":"Huan-Bo","family":"Luan","affiliation":""},{"name":"Maosong Sun","slug":"maosong-sun","given":"Maosong","family":"Sun","affiliation":""},{"name":"Tatsuya Izuha","slug":"tatsuya-izuha","given":"Tatsuya","family":"Izuha","affiliation":""},{"name":"Dakun Zhang","slug":"dakun-zhang","given":"Dakun","family":"Zhang","affiliation":""}],"abstract":"While parallel corpora are an indispensable resource for data-driven multilingual natural language processing tasks such as machine translation, they are limited in quantity, quality and coverage. As a result, learning translation models from non-parallel corpora has become increasingly important nowadays, especially for low-resource languages. In this work, we propose a joint model for iteratively learning parallel lexicons and phrases from nonparallel corpora. The model is trained using a Viterbi EM algorithm that alternates between constructing parallel phrases using lexicons and updating lexicons based on the constructed parallel phrases. Experiments on Chinese-English datasets show that our approach learns better parallel lexicons and phrases and improves translation performance significantly.","doi":null,"url":"https://ijcai.org/proceedings/2015/180","pdf":"https://ijcai.org/proceedings/2015/0180.pdf","markdown":"https://ijcai.org/proceedings/2015/180.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/180","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Natural Language Processing","track":"Main Track","number":180,"pages":{"first":1250,"last":1255},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}