Abstract
This paper discusses a segmentation approach of Mongolian for Cyrillic text for machine translation. Using this method, the processing of one-to-one word permutation between the variations of Mongolian and other languages, especially Altaic family languages like Japanese, becomes easier. Furthermore, it can be used for two-way conversion between texts of Mongolian used in different regions and counties, such as Mongolia and China. Our system has been implemented based on DP (dynamic programming) matching supported by knowledge-based sequence matching, referred to as a multilingual dictionary and linguistic rule bank (LRB), and a data-driven approach of the target language corpus (TLC). For convenience, NM (New Mongolian) is treated as the source language, and TM (Traditional Mongolian) and Todo as the target language in this test. Our application was tested using manually transcribed texts with sizes of 5, 000 sentences paralleled from NM to TM and Todo. We found that our method could achieve 91.9% of the transformation accuracy for “NM” to “TM” and 94.3% for “NM” to “Todo”.
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