Paper: Online Learning for Interactive Statistical Machine Translation

ACL ID N10-1079
Title Online Learning for Interactive Statistical Machine Translation
Venue Human Language Technologies
Session Main Conference
Year 2010
Authors

State-of-the-art Machine Translation (MT) systemsarestillfarfrombeingperfect. Anal- ternative is the so-called Interactive Machine Translation (IMT) framework. In this frame- work, the knowledge of a human translator is combined with a MT system. The vast ma- jority of the existing work on IMT makes use of the well-known batch learning paradigm. Inthebatchlearningparadigm,thetrainingof theIMTsystemandtheinteractivetranslation processarecarriedoutinseparatestages. This paradigm is not able to take advantage of the new knowledge produced by the user of the IMT system. In this paper, we present an ap- plication of the online learning paradigm to the IMT framework. In the online learning paradigm, the training and prediction stages are no longer separated. This feature is par- ticularlyusefuli...