Learning Head-modifier Pairs to Improve Lexicalized Dependency Parsing on a Chinese Treebank

Proceedings of the Sixth International Workshop on Treebanks and Linguistic Theories. Editors: Koenraad De Smedt, Jan Hajič and Sandra Kübler. NEALT Proceedings Series, Vol. 1 (2007), 201-212. © 2007 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/4476

Post-editing machine translated text in a commercial setting: Observation and statistical analysis

Machine translation systems, when they are used in a commercial context for publishing purposes, are usually used in combination with human post-editing. Thus understanding human post-editing behaviour is crucial in order to maximise the benefit of machine translation systems. Though there have been a number of studies carried out on human post-editing to date, there is a lack of large-scale studies on post-editing in industrial contexts which focus on the activity in real-life settings. This study observes professional Japanese post-editors’ work and examines the effect of the amount of editing made during post-editing, source text characteristics, and post-editing behaviour, on the amount of post-editing effort. A mixed method approach was employed to both quantitatively and qualitatively analyse the data and gain detailed insights into the post-editing activity from various view points. The results indicate that a number of factors, such as sentence structure, document component types, use of product specific terms, and post-editing patterns and behaviour, have effect on the amount of post-editing effort in an intertwined manner. The findings will contribute to a better utilisation of machine translation systems in the industry as well as the development of the skills and strategies of post-editors