Evaluation of domain adaptation approaches to improve the translation quality

This paper focuses on the usage of different domain adaptation methods to build a general purpose translation system for the languages with limited parallel training data. Several domain adaptation approaches are evaluated on four different domains in the English- Turkish SMT task. Our comparative experiments show that the language model adaptation gives the best performance and increases the translation success with a relative 9.25% improvement yielding 29.89 BLEU points on multi-domain test data.