Machine learning based english-to-Korean transliteration using grapheme and phoneme information

Machine transliteration is an automatic method to generate characters or words in one alphabetical system for the corresponding characters in another alphabetical system. Machine transliteration can play an important role in natural language application such as information retrieval and machine translation, especially for handling proper nouns and technical terms. The previous works focus on either a grapheme-based or phoneme-based method. However, transliteration is an orthographical and phonetic converting process. Therefore, both grapheme and phoneme information should be considered in machine transliteration. In this paper, we propose a grapheme and phoneme-based transliteration model and compare it with previous grapheme-based and phoneme-based models using several machine learning techniques. Our method shows about 13 similar to 78% performance improvement.
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Issue Date
2005-07
Language
ENG
Keywords

ALGORITHM

Citation

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E88D, no.7, pp.1737 - 1748

ISSN
0916-8532
DOI
10.1093/ietisy/e88-d.7.1737
URI
http://hdl.handle.net/10203/3582
Appears in Collection
CS-Journal Papers(저널논문)
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