{"type":"ScholarlyArticle","title":"Modeling Lexical Cohesion for Document-Level Machine Translation","authors":[{"name":"Deyi Xiong","slug":"deyi-xiong","given":"Deyi","family":"Xiong","affiliation":""},{"name":"Guosheng Ben","slug":"guosheng-ben","given":"Guosheng","family":"Ben","affiliation":""},{"name":"Min Zhang","slug":"min-zhang-2","given":"Min","family":"Zhang","affiliation":""},{"name":"Yajuan Lv","slug":"yajuan-lv","given":"Yajuan","family":"Lv","affiliation":""},{"name":"Qun Liu","slug":"qun-liu","given":"Qun","family":"Liu","affiliation":""}],"abstract":"Lexical cohesion arises from a chain of lexical items that establish links between sentences in a text. In this paper we propose three different models to capture lexical cohesion for document-level machine translation: (a) a direct reward model where translation hypotheses are rewarded whenever lexical cohesion devices occur in them, (b) a conditional probability model where the appropriateness of using lexical cohesion devices is measured, and (c) a mutual information trigger model where a lexical cohesion relation is considered as a trigger pair and the strength of the association between the trigger and the triggered item is estimated by mutual information. We integrate the three models into hierarchical phrase-based machine translation and evaluate their effectiveness on the NIST Chinese-English translation tasks with large-scale training data. Experiment results show that all three models can achieve substantial improvements over the baseline and that the mutual information trigger model performs better than the others.","doi":null,"url":"https://ijcai.org/proceedings/2013/322","pdf":"https://ijcai.org/proceedings/2013/0322.pdf","markdown":"https://ijcai.org/proceedings/2013/322.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/322","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":322,"pages":{"first":2183,"last":2188},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}