@inproceedings{mi-etal-2009-ict,
title = "The {ICT} statistical machine translation system for the {IWSLT} 2009",
author = "Mi, Haitao and
Li, Yang and
Xia, Tian and
Xiao, Xinyan and
Feng, Yang and
Xie, Jun and
Xiong, Hao and
Tu, Zhaopeng and
Zheng, Daqi and
Lu, Yanjuan and
Liu, Qun",
booktitle = "Proceedings of the 6th International Workshop on Spoken Language Translation: Evaluation Campaign",
month = dec # " 1-2",
year = "2009",
address = "Tokyo, Japan",
url = "https://aclanthology.org/2009.iwslt-evaluation.8",
pages = "55--59",
abstract = "This paper describes the ICT Statistical Machine Translation systems that used in the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2009. For this year{'}s evaluation, we participated in the Challenge Task (Chinese-English and English-Chinese) and BTEC Task (Chinese-English). And we mainly focus on one new method to improve single system{'}s translation quality. Specifically, we developed a sentence-similarity based development set selection technique. For each task, we finally submitted the single system who got the maximum BLEU scores on the selected development set. The four single translation systems are based on different techniques: a linguistically syntax-based system, two formally syntax-based systems and a phrase-based system. Typically, we didn{'}t use any rescoring or system combination techniques in this year{'}s evaluation.",
}
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<abstract>This paper describes the ICT Statistical Machine Translation systems that used in the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2009. For this year’s evaluation, we participated in the Challenge Task (Chinese-English and English-Chinese) and BTEC Task (Chinese-English). And we mainly focus on one new method to improve single system’s translation quality. Specifically, we developed a sentence-similarity based development set selection technique. For each task, we finally submitted the single system who got the maximum BLEU scores on the selected development set. The four single translation systems are based on different techniques: a linguistically syntax-based system, two formally syntax-based systems and a phrase-based system. Typically, we didn’t use any rescoring or system combination techniques in this year’s evaluation.</abstract>
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%0 Conference Proceedings
%T The ICT statistical machine translation system for the IWSLT 2009
%A Mi, Haitao
%A Li, Yang
%A Xia, Tian
%A Xiao, Xinyan
%A Feng, Yang
%A Xie, Jun
%A Xiong, Hao
%A Tu, Zhaopeng
%A Zheng, Daqi
%A Lu, Yanjuan
%A Liu, Qun
%S Proceedings of the 6th International Workshop on Spoken Language Translation: Evaluation Campaign
%D 2009
%8 dec 1 2
%C Tokyo, Japan
%F mi-etal-2009-ict
%X This paper describes the ICT Statistical Machine Translation systems that used in the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2009. For this year’s evaluation, we participated in the Challenge Task (Chinese-English and English-Chinese) and BTEC Task (Chinese-English). And we mainly focus on one new method to improve single system’s translation quality. Specifically, we developed a sentence-similarity based development set selection technique. For each task, we finally submitted the single system who got the maximum BLEU scores on the selected development set. The four single translation systems are based on different techniques: a linguistically syntax-based system, two formally syntax-based systems and a phrase-based system. Typically, we didn’t use any rescoring or system combination techniques in this year’s evaluation.
%U https://aclanthology.org/2009.iwslt-evaluation.8
%P 55-59
Markdown (Informal)
[The ICT statistical machine translation system for the IWSLT 2009](https://aclanthology.org/2009.iwslt-evaluation.8) (Mi et al., IWSLT 2009)
ACL
- Haitao Mi, Yang Li, Tian Xia, Xinyan Xiao, Yang Feng, Jun Xie, Hao Xiong, Zhaopeng Tu, Daqi Zheng, Yanjuan Lu, and Qun Liu. 2009. The ICT statistical machine translation system for the IWSLT 2009. In Proceedings of the 6th International Workshop on Spoken Language Translation: Evaluation Campaign, pages 55–59, Tokyo, Japan.