Yanqing He


2021

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ISTIC’s Triangular Machine Translation System for WMT2021
Hangcheng Guo | Wenbin Liu | Yanqing He | Tian Lan | Hongjiao Xu | Zhenfeng Wu | You Pan
Proceedings of the Sixth Conference on Machine Translation

This paper describes the ISTIC’s submission to the Triangular Machine Translation Task of Russian-to-Chinese machine translation for WMT’ 2021. In order to fully utilize the provided corpora and promote the translation performance from Russian to Chinese, the pivot method is used in our system which pipelines the Russian-to-English translator and the English-to-Chinese translator to form a Russian-to-Chinese translator. Our system is based on the Transformer architecture and several effective strategies are adopted to improve the quality of translation, including corpus filtering, data pre-processing, system combination and model ensemble.

2020

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ISTIC’s Neural Machine Translation System for IWSLT’2020
Jiaze Wei | Wenbin Liu | Zhenfeng Wu | You Pan | Yanqing He
Proceedings of the 17th International Conference on Spoken Language Translation

This paper introduces technical details of machine translation system of Institute of Scientific and Technical Information of China (ISTIC) for the 17th International Conference on Spoken Language Translation (IWSLT 2020). ISTIC participated in both translation tasks of the Open Domain Translation track: Japanese-to-Chinese MT task and Chinese-to-Japanese MT task. The paper mainly elaborates on the model framework, data preprocessing methods and decoding strategies adopted in our system. In addition, the system performance on the development set are given under different settings.

2010

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A Novel Reordering Model Based on Multi-layer Phrase for Statistical Machine Translation
Yanqing He | Yu Zhou | Chengqing Zong | Huilin Wang
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)

2008

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A Generalized Reordering Model for Phrase-Based Statistical Machine Translation
Yanqing He | Chengqing Zong
Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers

Phrase-based translation models are widely studied in statistical machine translation (SMT). However, the existing phrase-based translation models either can not deal with non-contiguous phrases or reorder phrases only by the rules without an effective reordering model. In this paper, we propose a generalized reordering model (GREM) for phrase-based statistical machine translation, which is not only able to capture the knowledge on the local and global reordering of phrases, but also is able to obtain some capabilities of phrasal generalization by using non-contiguous phrases. The experimental results have indicated that our model out- performs MEBTG (enhanced BTG with a maximum entropy-based reordering model) and HPTM (hierarchical phrase-based translation model) by improvement of 1.54% and 0.66% in BLEU.

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The CASIA statistical machine translation system for IWSLT 2008
Yanqing He | Jiajun Zhang | Maoxi Li | Licheng Fang | Yufeng Chen | Yu Zhou | Chengqing Zong
Proceedings of the 5th International Workshop on Spoken Language Translation: Evaluation Campaign

This paper describes our statistical machine translation system (CASIA) used in the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2008. In this year's evaluation, we participated in challenge task for Chinese-English and English-Chinese, BTEC task for Chinese-English. Here, we mainly introduce the overview of our system, the primary modules, the key techniques, and the evaluation results.

2007

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CASIA phrase-based SMT system for IWSLT’07
Yu Zhou | Yanqing He | Chengqing Zong
Proceedings of the Fourth International Workshop on Spoken Language Translation

2006

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NLPR translation system for IWSLT 2006 evaluation campaign
Chunguang Chai | Jinhua Du | Wei Wei | Peng Liu | Keyan Zhou | Yanqing He | Chengqing Zong
Proceedings of the Third International Workshop on Spoken Language Translation: Evaluation Campaign