Korean Morphological Analysis for Korean-Vietnamese Statistical Machine Translation

Quang-Phuoc Nguyen; Joon-Choul Shin; Cheol-Young Ock

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Korean Morphological Analysis for Korean-Vietnamese Statistical Machine Translation

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摘要

This paper describes the experiments with Korean-to-Vietnamese statistical machine translation (SMT). The fact that Korean is a morphologically complex language that does not have clear optimal word boundaries causes a major problem of translating into or from Korean. To solve this problem, we present a method to conduct a Korean morphological analysis by using a pre-analyzed partial word-phrase dictionary (PWD).Besides, we build a Korean-Vietnamese parallel corpus for training SMT models by collecting text from multilingual magazines. Then, we apply such a morphology analysis to Korean sentences that are included in the collected parallel corpus as a preprocessing step. The experiment results demonstrate a remarkable improvement of Korean-to-Vietnamese translation quality in term of bi-lingual evaluation understudy (BLEU).

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来源
《电子科技学刊：英文版》 |2017年第4期|P.413-419|共7页
作者
Quang-Phuoc Nguyen; Joon-Choul Shin; Cheol-Young Ock;
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作者单位

[1]Department of IT Convergence;

University of Ulsan;

Ulsan 44610;

Republic of Korea;

[1]Department of IT Convergence;

University of Ulsan;

Ulsan 44610;

Republic of Korea;

[1]Department of IT Convergence;

University of Ulsan;

Ulsan 44610;

Republic of Korea;

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原文格式 PDF
正文语种 CHI
中图分类基础理论;
关键词
Factored; translation; models; Korean-Vietnamese; parallel; corpus; morphological; analysis; statistical; machine; translation; (SMT);

机译：因子翻译;模型;韩越;平行;语料库;形态学;分析;统计;机器;翻译;（SMT）;

Korean Morphological Analysis for Korean-Vietnamese Statistical Machine Translation

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