Aji Prasetya Wibawa, Andrew Nafalski, Jeffrey Tweedale, Neil Murray, Ahmad Effendi Kadarisman
Javanese is a local language with the biggest number of speakers in Indonesia. However, the fact that it is characterized by a complex system of politeness means that it is perceived negatively by Javanese teenagers, who have difficulty understanding it. The hybrid corpus-based machine translation described here is designed to address this by offering a means of translating speech levels appropriately. The system embeds statistical features into a memory-based machine translation to obtain the best performance of Javanese speech levels' translation. The evaluation shows satisfactory results; 0.83 and 90.4 for the average accuracy and quality of the translation, respectively. ©2013 IEEE.
School of Electrical and Information Engineering, University of South Australia, Adelaide, SA, Australia; Centre for Applied Linguistics, Warwick University, Warwick, United Kingdom; Faculty of Letters, State University of Malang, Malang, Indonesia
