LIMSI Submission for the WMT'13 Quality Estimation Task: an Experiment with N-Gram Posteriors
Anil Kumar Singh, Guillaume Wisniewski, François Yvon · 2013
This paper describes the machine learning algorithm and the features used by LIMSI for the Quality Estimation Shared Task. Our submission mainly aims at evaluating the usefulness for quality estimation of n-gram posterior probabilities that quantify the probability for a given n-gram to be part of the system output. 1