Identifying Useful Human Correction Feedback from an On-line Machine Translation Service

Alberto Barrón-Cedeño

Omega-S208 Campus Nord - UPC

Mon Apr 22, 2013

from 14:30h to 15:00h


Post-editing feedback provided by users of online translation services offers a good opportunity for the improvement of statistical machine translation systems. However, feedback provided by casual users is noisy, and must be filtered in order to identify potentially useful instances. In this talk I present our recent study on automatic feedback filtering from a real weblog. I will discuss on the features we have considered to decide whether a user's translation proposal is indeed better than the one automatically generated. Regardless of the inherent difficulty of the task (even for humans!), I will show how the selected instances allow to improve the performance of a phrase-based translation system.


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