title: Statistical machine translation for biomedical text: are we there yet?
abstract: In our paper we addressed the research question: "Has machine translation achieved sufficiently high quality to translate PubMed titles for patients?". We analyzed statistical machine translation output for six foreign language - English translation pairs (bi-directionally). We built a high performing in-house system and evaluated its output for each translation pair on large scale both with automated BLEU scores and human judgment. In addition to the in-house system, we also evaluated Google Translate's performance specifically within the biomedical domain. We report high performance for German, French and Spanish -- English bi-directional translation pairs for both Google Translate and our system.
authors.affiliation: University of Washington, Seattle, WA, USA. cuijunwu@uw.edu
authors.forename: Cuijun
authors.initials: C
authors.lastname: Wu
authors.forename: Fei
authors.initials: F
authors.lastname: Xia
authors.forename: Louise
authors.initials: L
authors.lastname: Deleger
authors.forename: Imre
authors.initials: I
authors.lastname: Solti
mesh_terms: D001185:Artificial Intelligence; D009323:Natural Language Processing; D039781:PubMed; D057386:Search Engine; D014175:Translating