Liang Tian


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UM-Corpus: A Large English-Chinese Parallel Corpus for Statistical Machine Translation
Liang Tian | Derek F. Wong | Lidia S. Chao | Paulo Quaresma | Francisco Oliveira | Yi Lu | Shuo Li | Yiming Wang | Longyue Wang
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Parallel corpus is a valuable resource for cross-language information retrieval and data-driven natural language processing systems, especially for Statistical Machine Translation (SMT). However, most existing parallel corpora to Chinese are subject to in-house use, while others are domain specific and limited in size. To a certain degree, this limits the SMT research. This paper describes the acquisition of a large scale and high quality parallel corpora for English and Chinese. The corpora constructed in this paper contain about 15 million English-Chinese (E-C) parallel sentences, and more than 2 million training data and 5,000 testing sentences are made publicly available. Different from previous work, the corpus is designed to embrace eight different domains. Some of them are further categorized into different topics. The corpus will be released to the research community, which is available at the NLP2CT website.

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Toward Better Chinese Word Segmentation for SMT via Bilingual Constraints
Xiaodong Zeng | Lidia S. Chao | Derek F. Wong | Isabel Trancoso | Liang Tian
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)


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Influence of Part-of-Speech and Phrasal Category Universal Tag-set in Tree-to-Tree Translation Models
Francisco Oliveira | Derek F. Wong | Lidia S. Chao | Liang Tian | Liangye He
Proceedings of the Sixth International Joint Conference on Natural Language Processing


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Word Alignment Using GIZA++ on Windows
Liang Tian | Fai Wong | Sam Chao
Proceedings of Machine Translation Summit XIII: System Presentations