PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Human interaction for high quality machine translation.
Francisco Casacuberta, Jorge Civera, E. Cubel, A.L. Lagarda, G. Lapalme, E. Macklovitch and Enrique Vidal
Communications of the ACM Volume 10, Number 52, pp. 135-138, 2009.

Abstract

In the TT2 project, a full-fledged MT engine was embedded in an interactive editing environment and used to generate suggested completions of each target sentence being translated. These completions may be accepted or amended by the translator; but once validated, they are exploited by the MT engine to produce further, hopefully improved suggestions. This is in marked contrast with traditional MT, where typically the system is first used to produce a complete draft translation of a source text, which is then post-edited (i.e. corrected) off-line by a human translator. TT2's interactive approach offers a significant advantage over traditional post-editing. In the latter paradigm, there is no way for the system, which is off-line, to benefit from the user's corrections; in TransType, just the opposite is true. As soon as the user begins to revise an incorrect segment, the system immediately responds to that new information by proposing an alternative completion to the target segment, which is compatible with the prefix that the user has input.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:User Modelling for Computer Human Interaction
Natural Language Processing
ID Code:5713
Deposited By:Alfons Juan
Deposited On:08 March 2010