Text conversion system between Turkic dialects

Turkic communities come from a common culture; however the interaction with other communities over years caused diversion especially in written language. A system which can automatically translate documents written in different Turkic languages will be an important step towards eliminating the disunity of Turkic communities on written work of art over past ninety years and obtaining fusion of Turkic communities. In this study, a rule-based and semi-supervised machine translation system (MT-Turk), which is designed for closely related Turkic languages and implemented on Turkish, Kirghiz and Kazan Tatar, is presented. MT-Turk is an extensible bidirectional translation infrastructure in which new Turkic dialects can be added by just adding the lexicon of roots/stems, suffixes, and the rules. Furthermore, it is open to extension by suggestion. In order to form a multilingual machine translation infrastructure, two subsets of rule-based approach, the interlingual machine translation approach and transfer-based approach were used in combination to achieve extensibility and interoperability. The success of the translation process was evaluated using both BLEU and NIST metrics. The evaluated scores were between 5.04 and 15.12 for BLEU, between 3.12 and 4.64 for NIST in unsupervised translation and between 7.20 and 21.71 for BLEU, between 3.52 and 4.77 for NIST in semi-supervised translation for various language pairs and translation directions. Depending on these results, it was seen that the efficiency of the translation process is extremely dependent on the size of the lexicon and the rule base. Keywords: Machine translation, natural language processing, rule-based machine translation, multi-word expressions, Turkic dialects, Turkish, Kirghiz, Kazan Tatar