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http://dx.doi.org/10.3745/KIPSTB.2004.11B.3.387

Construction of Linearly Aliened Corpus Using Unsupervised Learning  

Lee, Kong-Joo (경인여자대학 컴퓨터정보기술학부)
Kim, Jae-Hoon (한국해양대학교 컴퓨터공학과)
Publication Information
The KIPS Transactions:PartB / v.11B, no.3, 2004 , pp. 387-394 More about this Journal
Abstract
In this paper, we propose a modified unsupervised linear alignment algorithm for building an aligned corpus. The original algorithm inserts null characters into both of two aligned strings (source string and target string), because the two strings are different from each other in length. This can cause some difficulties like the search space explosion for applications using the aligned corpus with null characters and no possibility of applying to several machine learning algorithms. To alleviate these difficulties, we modify the algorithm not to contain null characters in the aligned source strings. We have shown the usability of our approach by applying it to different areas such as Korean-English back-trans literation, English grapheme-phoneme conversion, and Korean morphological analysis.
Keywords
Unsupervised Learning; Edit Distance; Linear Alignment; Korean-English(back) Transliteration; Grapheme-Phoneme Conversion; Korean Morphological Segmentation;
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