The use of recurrent neural networks language model in Turkish-English machine translation

Turkish with its agglutinative structure needs speacial attention in machine translation research. In this work, a Turkish-English machine translation system is developed for TED¹ talks with hierarchical phrase-based machine translation by employing morphological representation for Turkish. Then it is aimed to improve the translation performance by utilizing n-best rescoring with recurrent neural network language model and system combination together.