LORIA System for the WMT13 Quality Estimation Shared Task

In this paper we present the system we submitted to the WMT13 shared task on Quality Estimation. We participated in the Task 1.1. Each translated sentence is given a score between 0 and 1. The score is obtained by using several numerical or boolean features calculated according to the source and target sentences. We perform a linear regression of the feature space against scores in the range [0..1]. To this end, we use a Support Vector Machine with 66 features. In this paper, we propose to increase the size of the training corpus. For that, we use the post-edited and reference corpora during the training step. We assign a score to each sentence of these corpora. Then, we tune these scores on a development corpus. This leads to an improvement of 10.5% on the development corpus, in terms of Mean Average Error, but achieves only a slight improvement on the test corpus.