Thomas C. Chuang


2005

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Aligning Parallel Bilingual Corpora Statistically with Punctuation Criteria
Thomas C. Chuang | Kevin C. Yeh
International Journal of Computational Linguistics & Chinese Language Processing, Volume 10, Number 1, March 2005

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Collocational Translation Memory Extraction Based on Statistical and Linguistic Information
Thomas C. Chuang | Jia-Yan Jian | Yu-Chia Chang | Jason S. Chang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 10, Number 3, September 2005: Special Issue on Selected Papers from ROCLING XVI

2004

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Subsentential Translation Memory for Computer Assisted Writing and Translation
Jian-Cheng Wu | Thomas C. Chuang | Wen-Chi Shei | Jason S. Chang
Proceedings of the ACL Interactive Poster and Demonstration Sessions

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Alignment of bilingual named entities in parallel corpora using statistical model
Chun-Jen Lee | Jason S. Chang | Thomas C. Chuang
Proceedings of the 6th Conference of the Association for Machine Translation in the Americas: Technical Papers

Named entities make up a bulk of documents. Extracting named entities is crucial to various applications of natural language processing. Although efforts to identify named entities within monolingual documents are numerous, extracting bilingual named entities has not been investigated extensively owing to the complexity of the task. In this paper, we describe a statistical phrase translation model and a statistical transliteration model. Under the proposed models, a new method is proposed to align bilingual named entities in parallel corpora. Experimental results indicate that a satisfactory precision rate can be achieved. To enhance the performance, we also describe how to improve the proposed method by incorporating approximate matching and person name recognition. Experimental results show that performance is significantly improved with the enhancement.

2003

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Interleaving Text and Punctuations for Bilingual Sub-sentential Alignment
Wen-Chi Hsie | Kevin Yeh | Jason S. Chang | Thomas C. Chuang
ROCLING 2003 Poster Papers

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Using Punctuations and Lengths for Bilingual Sub-sentential Alignment
Wen-Chi Hsien | Kevin Yeh | Jason S. Chang | Thomas C. Chuang
ROCLING 2003 Poster Papers

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Building A Chinese WordNet Via Class-Based Translation Model
Jason S. Chang | Tracy Lin | Geeng-Neng You | Thomas C. Chuang | Ching-Ting Hsieh
International Journal of Computational Linguistics & Chinese Language Processing, Volume 8, Number 2, August 2003

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TotalRecall: A Bilingual Concordance for Computer Assisted Translation and Language Learning
Jian-Cheng Wu | Kevin C. Yeh | Thomas C. Chuang | Wen-Chi Shei | Jason S. Chang
The Companion Volume to the Proceedings of 41st Annual Meeting of the Association for Computational Linguistics

2002

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Adaptive bilingual sentence alignment
Thomas C. Chuang | G.N. You | Jason Chang
Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: Technical Papers

We present a new approach to the problem of aligning English and Chinese sentences in a bilingual corpus based on adaptive learning. While using length information alone produces surprisingly good results for aligning bilingual French and English sentences with success rates well over 95%, it does not fair as well for the alignment of English and Chinese sentences. The crux of the problem lies in greater variability of lengths and match types of the matched sentences. We propose to cope with such variability via a two-pass scheme under which model parameters can be learned from the data at hand. Experiments show that under the approach bilingual English-Chinese texts can be aligned effectively across diverse domains, genres and translation directions with accuracy rates approaching 99%.