NDLI: Does joint decoding really outperform cascade processing in English-to-Chinese transliteration generation? The role of syllabification

Content Provider	IEEE Xplore Digital Library
Author	Yan Song Chunyu Kit
Copyright Year	2010
Description	Author affiliation: Department of Chinese, Translation and Linguistics, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong (Yan Song; Chunyu Kit)
Abstract	Transliteration is a challengeable task aimed at converting a proper name into another language with phonetic equivalence. Since the conversion relates to the phonetic aspect of a text, syllabification is considered a major factor affecting the performance of a transliteration system. In grapheme-based approaches, there are two routines to transliterate, one is to perform in a pipeline of separate syllabification and other components in generation process step by step, the other is to synchronously segment syllables and generating transliteration options. Usually, joint decoding outperforms the cascade processing in many natural language processing missions, however, syllabification is a special component in transliteration task. Thus in this paper, we investigate the two routines with a systematic analysis and compare their results to illustrate the strength of syllabification. A phrase-based statistical machine translation framework for joint decoding and a conditional random field syllabification system are used in this work for our investigation, which shows a different scenario on the issue of joint decoding versus cascade processing in transliteration.
Starting Page	3323
Ending Page	3328
File Size	356935
Page Count	6
File Format	PDF
ISBN	9781424465262
e-ISBN	9781424465279
DOI	10.1109/ICMLC.2010.5580674
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decoding Testing Feature extraction Training Accuracy Joints log-linear model Transliteration syllabification joint decoding statistical machine translation
Content Type	Text
Resource Type	Article

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