The usage of differential evolution in a statistical machine translation

Translations in statistical machine translation (SMT) are generated on the basis of statistical models, the parameters of which are derived from the analysis of aligned bilingual text corpora. Different models' parameters provide various translations, which can be evaluated by the BiLingual Evaluation Understudy (BLEU) metric. The problem of finding a suitable translation can be regarded as an optimization problem and some optimization can be done using the decoder itself - the optimization of models parameters. The main goal of this paper was to build SMT systems for the language pair English- Slovenian, and improve their translation quality using a global optimization algorithm - Differential Evolution (DE) algorithm. Experiments were performed using English and Slovenian JRCACQUIS Multilingual Parallel Corpora. The results show improvement in the translation quality.