The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Susunan perkataan adalah salah satu perbezaan yang paling ketara antara orang Cina dan Vietnam. Dalam terjemahan mesin statistik berasaskan frasa, model penyusunan semula akan mempelajari peraturan penyusunan semula daripada korpora dwibahasa. Jika korpora dwibahasa adalah besar dan cukup baik, peraturan penyusunan semula adalah tepat dan boleh dilindungi. Walau bagaimanapun, bahasa Cina-Vietnam ialah pasangan bahasa sumber rendah, pengekstrakan peraturan penyusunan semula adalah terhad. Ini membawa kepada kualiti penyusunan semula dalam terjemahan mesin Cina-Vietnam tidak tinggi. Dalam kertas kerja ini, kami telah menggabungkan hubungan pergantungan Cina dan hasil penjajaran perkataan Cina-Vietnam untuk membuat prapesan susunan perkataan Cina agar sesuai dengan susunan perkataan Vietnam. Keputusan eksperimen menunjukkan bahawa metodologi kami telah meningkatkan prestasi terjemahan mesin berbanding sistem terjemahan hanya menggunakan model penyusunan semula terjemahan mesin statistik berasaskan frasa.
Huu-Anh TRAN
Beijing Institute of Technology
Heyan HUANG
Beijing Institute of Technology
Phuoc TRAN
Ton Duc Thang University
Shumin SHI
Beijing Institute of Technology
Huu NGUYEN
Ho Chi Minh City University of Food Industry
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Salinan
Huu-Anh TRAN, Heyan HUANG, Phuoc TRAN, Shumin SHI, Huu NGUYEN, "Preordering for Chinese-Vietnamese Statistical Machine Translation" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 2, pp. 375-382, February 2019, doi: 10.1587/transinf.2018EDP7211.
Abstract: Word order is one of the most significant differences between the Chinese and Vietnamese. In the phrase-based statistical machine translation, the reordering model will learn reordering rules from bilingual corpora. If the bilingual corpora are large and good enough, the reordering rules are exact and coverable. However, Chinese-Vietnamese is a low-resource language pair, the extraction of reordering rules is limited. This leads to the quality of reordering in Chinese-Vietnamese machine translation is not high. In this paper, we have combined Chinese dependency relation and Chinese-Vietnamese word alignment results in order to pre-order Chinese word order to be suitable to Vietnamese one. The experimental results show that our methodology has improved the machine translation performance compared to the translation system using only the reordering models of phrase-based statistical machine translation.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDP7211/_p
Salinan
@ARTICLE{e102-d_2_375,
author={Huu-Anh TRAN, Heyan HUANG, Phuoc TRAN, Shumin SHI, Huu NGUYEN, },
journal={IEICE TRANSACTIONS on Information},
title={Preordering for Chinese-Vietnamese Statistical Machine Translation},
year={2019},
volume={E102-D},
number={2},
pages={375-382},
abstract={Word order is one of the most significant differences between the Chinese and Vietnamese. In the phrase-based statistical machine translation, the reordering model will learn reordering rules from bilingual corpora. If the bilingual corpora are large and good enough, the reordering rules are exact and coverable. However, Chinese-Vietnamese is a low-resource language pair, the extraction of reordering rules is limited. This leads to the quality of reordering in Chinese-Vietnamese machine translation is not high. In this paper, we have combined Chinese dependency relation and Chinese-Vietnamese word alignment results in order to pre-order Chinese word order to be suitable to Vietnamese one. The experimental results show that our methodology has improved the machine translation performance compared to the translation system using only the reordering models of phrase-based statistical machine translation.},
keywords={},
doi={10.1587/transinf.2018EDP7211},
ISSN={1745-1361},
month={February},}
Salinan
TY - JOUR
TI - Preordering for Chinese-Vietnamese Statistical Machine Translation
T2 - IEICE TRANSACTIONS on Information
SP - 375
EP - 382
AU - Huu-Anh TRAN
AU - Heyan HUANG
AU - Phuoc TRAN
AU - Shumin SHI
AU - Huu NGUYEN
PY - 2019
DO - 10.1587/transinf.2018EDP7211
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2019
AB - Word order is one of the most significant differences between the Chinese and Vietnamese. In the phrase-based statistical machine translation, the reordering model will learn reordering rules from bilingual corpora. If the bilingual corpora are large and good enough, the reordering rules are exact and coverable. However, Chinese-Vietnamese is a low-resource language pair, the extraction of reordering rules is limited. This leads to the quality of reordering in Chinese-Vietnamese machine translation is not high. In this paper, we have combined Chinese dependency relation and Chinese-Vietnamese word alignment results in order to pre-order Chinese word order to be suitable to Vietnamese one. The experimental results show that our methodology has improved the machine translation performance compared to the translation system using only the reordering models of phrase-based statistical machine translation.
ER -