Name
Abstract | ||
|---|---|---|
This paper addresses a Korean-English machine translation system for scientific papers. The MT system is supported by CL (Controlled
Language)-guided source language rewriting. After analyzing the translation errors of the system, we defined Korean rewriting
rules to avoid the linguistic obstacles that may affect the translation accuracy. To support this, a Korean CL-checker was
implemented. We showed that this CL-guided MT system can improve the translation accuracy by about 13% by adopting CL rewriting
rules. However, this improvement is still not enough for various purposes, because most of the users of the MT system may
want to submit the translated texts to a conference or an academic journal. As the MT output contains erroneous expressions,
a language model module was added to the pattern-based MT engine. The system automatically detects expressions with low frequency
and asks the authors to examine the translation. By adopting CL rewriting rules and language model module to the existing
MT engine, almost “professional” translations can be obtained.
|
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-70939-8_36 | CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing |
Keywords | Field | DocType |
translation error,mt output,language model module,pattern-based mt engine,source language,cl-guided mt system,translation accuracy,mt system,scientific papers,cl-guided korean-english mt system,existing mt engine,korean-english machine translation system,language model,low frequency,machine translation | Rule-based machine translation,Parse tree,Expression (mathematics),Computer science,Machine translation,Artificial intelligence,Rewriting,Transfer-based machine translation,Natural language processing,Computer-assisted translation,Language model | Conference |
Volume | ISSN | Citations |
4394 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Young-Kil Kim | 1 | 2 | 3.39 |
| Munpyo Hong | 2 | 7 | 4.70 |
| Sang Kyu Park | 3 | 28 | 12.49 |