Journal Article


Andy Way
Joss Moorkens



translation memory confidence estimation technology human evaluation machine translating statistical mt smt machine translation

Comparing translator acceptability of TM and SMT outputs (2016)

Abstract This paper reports on an initial study that aims to understand whether the acceptability of translation memory (TM) among translators when contrasted with machine translation (MT) unacceptability is based on users’ ability to optimise precision in match suggestions. Seven translators were asked to rate whether 60 English-German translated segments were a usable basis for a good target translation. 30 segments were from a domain-appropriate TM without a quality threshold being set, and 30 segments were translated by a general domain statistical MT system. Participants found the MT output more useful on average, with only TM fuzzy matches of over 90% considered more useful. This result suggests that, were the MT community able to provide an accurate quality threshold to users, they would consider MT to be the more useful technology.
Collections Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: ADAPT
Ireland -> Dublin City University -> Publication Type = Article
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating

Full list of authors on original publication

Andy Way, Joss Moorkens

Experts in our system

Andy Way
Dublin City University
Total Publications: 229
Joss Moorkens
Dublin City University
Total Publications: 17