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In this paper, we discuss a method of a textual transformation between the similar languages taking Mongolian as an example. The textual transformation approach is performed by combining a knowledge-based rule bank with data driven method. DP algorithm (dynamic programming) is applied to matching of the source and target language words. Our experimental results demonstrate that the proposed method has achieved 83.9% transformation accuracy (in F-measure) from NM (Cyrillic) to TM (Traditional Mongolian) text, and 88.1% for NM to TODO. KEYWORD: Mongolian language; similar language cross processing; data-driven approach; knowledgebased rule bank; DP algorithm International Conference on Industrial Technology and Management Science (ITMS 2015) © 2015. The authors Published by Atlantis Press 786 In Fig. 1, (a) TM (written by the traditional Mongolian scripts, found at the 13 th century) is nowadays used mainly in the area of the inner Mongolia; (b) TODO (written by called TODO scripts, found at the 17 th century) is used mainly in the Xinjiang area in China and Kalmyk in Russia; and (c) Cyrillic (writing by Cyrillic alphabet, found at the beginning of 20 th century ), is used in Mongolia and other areas such as Kalmyk and Buryat in Russia today. The sentence order and SOV structure (subject, predicate, object and verb) are same. But the rule of building a word and a way using the function words (suffixes or affixes) are different. An example of the sentence alignment by words of TODO and TM is illustrated in figure 2. Figure 2 a sentence and word alignment by TODO and TM Similarly, a phrase transformation pair of TM and NM is shown in figure 3. As shown in Fig.2 and Fig.3, we observe that a word, in either TODO or Cyrillic, corresponds to two or more words of TM, and there is a clear difference in the word formation and sequence. This means that it is quite difficult to transcribe the multi-graphic documents between Mongolian by a script (Unicode) unit or word unit. And as shown in Fig. 4, some words, especially in a case of TODO and NM, are very similar when the word is converted into nominal character (Latin or Unicode) forms. Figure 3 a phrase (NP) by TM and Cyrillic Figure 4 same words [Unicode] by different scripts To create word-to-word alignments and transformation, some rule based and statistical processing, such as segmentation of the suffixes and syntactic analysis of root word in the case of NM and TODO, will be necessary for Mongolian. Currently, researches related to the Mongolian natural language processing, especially a textual transformation among their texts are rare. T.ISHIKAWA research group introduced a performance based on the fundamental linguistic rules and a character unit for converting Cyrillic to TM texts and vice versa [6]. Although satisfactory conversion results have been reported, the authors also pointed that it was rather difficult to use their approach when the source languages were different and when out-of-rule (OOV) words occurred frequently. The report [7] challenged a transformation method between TM and NM two scripts based on the linguistic rules. However, it has been reported that the method has limited capability to transform others, such as TM. Additionally, the method cannot be used in the case of unlisted words in a limited corpus.

Reflection on Textual Transformation between the Similar Languages