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Real-life translation quality estimation for MT system selection

Authors :
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural
Formiga Fanals, Lluís
Màrquez Villodre, Lluís
Pujantell Traserra, Jaume
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural
Formiga Fanals, Lluís
Màrquez Villodre, Lluís
Pujantell Traserra, Jaume
Publication Year :
2013

Abstract

Research on translation quality annotation and estimation usually makes use of standard language, sometimes related to a specific language genre or domain. However, real-life machine translation (MT), performed for instance by on-line translation services, has to cope with some extra dif- ficulties related to the usage of open, non-standard and noisy language. In this paper we study the learning of quality estimation (QE) models able to rank translations from real-life input according to their goodness without the need of translation references. For that, we work with a corpus collected from the 24/7 Reverso.net MT service, translated by 5 different MT systems, and manually annotated with quality scores. We define several families of features and train QE predictors in the form of regressors or direct rankers. The predictors show a remarkable correlation with gold standard rankings and prove to be useful in a system combination scenario, obtaining better results than any individual translation system.<br />Peer Reviewed<br />Postprint (published version)

Details

Database :
OAIster
Notes :
8 p., application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1132971571
Document Type :
Electronic Resource