A Practical of Memory-based Approach for Improving Accuracy of MT
Sitthaa Phaholphinyo | Teerapong Modhiran | Nattapol Kritsuthikul | Thepchai Supnithi
Proceedings of Machine Translation Summit X: Papers
Rule-Based Machine Translation (RBMT)  approach is a major approach in MT research. It needs linguistic knowledge to create appropriate rules of translation. However, we cannot completely add all linguistic rules to the system because adding new rules may cause a conflict with the old ones. So, we propose a memory based approach to improve the translation quality without modifying the existing linguistic rules. This paper analyses the translation problems and shows how this approach works.
This paper presents an online Thai-English MT system, called PARSITTE, which is an extension of PARSIT English-Thai one. We aim to assist foreigners and Thai in exchanging more easily their information. The system is a rule-based and Interlingua approach. To improve the system, we concentrate on pre-processing and rule analysis phases, which are considered necessary because of some specific problems of Thai language.