{"type":"ScholarlyArticle","title":"Local Translation Prediction with Global Sentence Representation","authors":[{"name":"Jiajun Zhang","slug":"jiajun-zhang-2","given":"Jiajun","family":"Zhang","affiliation":""},{"name":"Dakun Zhang","slug":"dakun-zhang","given":"Dakun","family":"Zhang","affiliation":""},{"name":"Jie Hao","slug":"jie-hao","given":"Jie","family":"Hao","affiliation":""}],"abstract":"Statistical machine translation models have made great progress in improving the translation quality. However, the existing models predict the target translation with only the source- and target-side local context information. In practice, distinguishing good translations from bad ones does not only depend on the local features, but also rely on the global sentence-level information. In this paper, we explore the source-side global sentence-level features for target-side local translation prediction. We propose a novel bilingually-constrained chunk-based convolutional neural network to learn sentence semantic representations. With the sentence-level feature representation, we further design a feed-forward neural network to better predict translations using both local and global information. The large-scale experiments show that our method can obtain substantial improvements in translation quality over the strong baseline: the hierarchical phrase-based translation model augmented with the neural network joint model.","doi":null,"url":"https://ijcai.org/proceedings/2015/201","pdf":"https://ijcai.org/proceedings/2015/0201.pdf","markdown":"https://ijcai.org/proceedings/2015/201.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/201","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":201,"pages":{"first":1398,"last":1403},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}