Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
10-2004
Abstract
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.
Discipline
Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
Proceedings of the First Asia Information Retrieval Symposium (AIRS 2004)
First Page
106
Last Page
117
Identifier
10.1007/978-3-540-31871-2_10
Publisher
Springer
City or Country
Beijing, China
Citation
GAO, Wei; WONG, Kam-Fai; and LAM, Wai.
Improving transliteration with precise alignment of phoneme chunks and using contextual features. (2004). Proceedings of the First Asia Information Retrieval Symposium (AIRS 2004). 106-117.
Available at: https://ink.library.smu.edu.sg/sis_research/4631
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-3-540-31871-2_10