Improving transliteration with precise alignment of phoneme chunks and using contextual features

• Main Authors: GAO, Wei, WONG, Kam-Fai, LAM, Wai
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2004
• Subjects: Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/4631; https://ink.library.smu.edu.sg/context/sis_research/article/5634/viewcontent/Gao2005_Chapter_ImprovingTransliterationWithPr__1_.pdf
• Institution: Singapore Management University

Automatic transliteration of foreign names is basically regarded as a diminutive clone of the machine translation (MT) problem. It thus follows IBM’s conventional MT models under the sourcechannel framework. Nonetheless, some parameters of this model dealing with zero-fertility words in the target sequences, can negatively impact transliteration effectiveness because of the inevitable inverted conditional probability estimation. Instead of source-channel, this paper presents a direct probabilistic transliteration model using contextual features of phonemes with a tailored alignment scheme for phoneme chunks. Experiments demonstrate superior performance over the source-channel for the task of English-Chinese transliteration.