Abstract—In this paper, an effective machine translation system from Thai to Khmer language on a website is proposed. To create a web application for a high performance Thai-Khmer machine translation (ThKh-MT), the principles and methods of translation involve with lexical base. Word reordering is applied by considering the previous word, the next word and subject-verb agreement. The word adjustment is also required to attain acceptable outputs. Additional steps related to structure patterns are added in a combination with the classical methods to deal with translation issues. PHP is implemented to build the application with MySQL as a tool to create lexical databases. For testing, 5,100 phrases and sentences are selected to evaluate the system. The result shows 89.25 percent of accuracy and 0.84 for F-Measure which infers to a higher efficiency than that of Google and other systems. Index Terms—Thai Khmer translation, machine translation (MT), rule based, pattern-based. I. INTRODUCTION Association of Southeast Asian Nations (ASEAN) consists of ten countries with various cultures and languages. Thailand and Cambodia are included in ASEAN, and the eastern border of Thailand is adjacent to Cambodia. Therefore, efficient communication is significant for international relations between these two countries. Cambodian natives have Khmer as a national language while formal language in Thailand is Thai. The linguistic differences of Thai and Khmer in both writing and speaking contribute to a translation barrier. For instance, since Thai language has been adapted partly from Pali, Sanskrit and Old Khmer, Thai vocabulary is relatively diverse. Thai language also contains complex orthography and relational markers. Furthermore, standard written Thai is complicated due to various combinations of syllabic alphabets, which consists of 44 basic consonants, 21 vowel symbols and 4 tone diacritics, applied under the rule that all diacritics appear in front of, above or below the consonants. Furthermore, Thai syntax has a noun classifier system as well as conforms to a basic sentence structure called subject–verb–object (SVO) with a horizontal and vertical writing direction from left to right and from top to bottom, respectively. Similarly, Khmer contains 33 consonants, 23 dependent vowels and 15 independent vowels; however, no tone is presented. Due to the linguistic differences, current Thai-Khmer translation systems have scarcely achieved complete and accurate outputs. Moreover, Manuscript received August 15, 2016; revised December 1, 2016. The authors are with School of Information and Communication Technology, University of Phayao, 56000, Thailand, (e-mail: sukchatri.pr@up.ac.th, skchatri@hotmail.com, puthymol@gmail.com). the existent systems have rarely been created and developed. There is also a shortage of intellectuals who are competent in both languages and able to convey knowledge for creating a system of translation. As a result, the improvement of the Thai-Khmer translation system has been disrupted. Document translation between Thai and Khmer which requires high accuracy has consequently encountered difficulties. To solve the issues, machine translation (MT) from Thai to Khmer language requires development. The proposed system in this paper implements translation techniques including rule-based algorithm with verification of sentence patterns to improve translation quality. The overview operation of the translation system is to input a Thai language text in a web application and then convert it into a desired output in Khmer. A lexical analyzer is first applied in the process to divide Thai sentences or phrases into individual syllabic words so that the separated words are analyzed and processed in the following steps resulting in Khmer sentences. II. RELATED AND PREVIOUS WORKS There have been many attempts to research on machine translation between Thai and other languages. English-Thai machine translation was developed in 1998 with regard to the sentence-based technique which combines the rule-based and the example-based method to establish a system for English to Thai sentence translation [1]. However, the research result of performance evaluation and comparison was not indicated. In 2012, a technique called generalized patterns is presented to improve machine translation from Japanese to Thai language [2]. The method was compared to the others implemented in Google and Bing translators by executing 3,107 Japanese sentences in testing. F-Measure score was applied to assess performance of the translator. Machine translation between Khmer and other language has also been researched. One of the studies selected Moses DoMY CE, which is statistical machine translation (SMT), as a tool to create an online system for English - Khmer translation based on Python, XML and HTML language in 2013 [3]. There is also research in 2014 on developing a French-Khmer dictionary called „MotàMot‟ [4]. In 2015, an automatic machine translation was created to provide translation between Khmer and other 20 languages by using three statistical methods: the phrase-based approach, the hierarchical phrase-based approach and the operation sequence model (OSM) as well as selecting BLEU and RIBES to evaluate translation quality [5]. There is, furthermore, research specifically on Thai-Khmer machine translation. For example, Thai - Khmer machine translation on a website has been developed based Thai to Khmer Rule-Based Machine Translation Using Reordering Word to Phrase Sukchatri Prasomsuk and Puthy Mol International Journal of Computer Theory and Engineering, Vol. 9, No. 3, June 2017 223 DOI: 10.7763/IJCTE.2017.V9.1142