Ohnmar Htun

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This paper contributes a study of methods for integrating human expert knowledge with machine learning approaches for determining phonetic similarity of word pairs. A method is proposed which allows a human to provide a structure for the edit costs that are based around a phonetically-motivated model of phoneme sound groups, and the machine to determine(More)
This study aims to develop a phonetic similarity measurement method across Asian languages. The method, cross-language similarity algorithm aggregates the transcription of language-specific Romanization, the International Phonetic Alphabet, the Soundex algorithm, and Levenshtein distance. To evaluate the proposed algorithm, this study involves an experiment(More)
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