Paper: Balancing User Effort and Translation Error in Interactive Machine Translation via Confidence Measures

ACL ID P10-2032
Title Balancing User Effort and Translation Error in Interactive Machine Translation via Confidence Measures
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2010
Authors

This work deals with the application of confidence measures within an interactive- predictive machine translation system in order to reduce human effort. If a small loss in translation quality can be tolerated for the sake of efficiency, user effort can be saved by interactively translating only those initial translations which the confi- dence measure classifies as incorrect. We apply confidence estimation as a way to achieve a balance between user effort sav- ings and final translation error. Empiri- cal results show that our proposal allows to obtain almost perfect translations while significantly reducing user effort.