A Simple, Straightforward and Effective Model for Joint Bilingual Terms Detection and Word Alignment in SMT

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A Simple, Straightforward and Effective Model for Joint Bilingual Terms Detection and Word Alignment in SMT
Authors
Guoping Huang
Jiajun Zhang
Yu Zhou
Chengqing Zong
Publication date
2016
ISSN
03029743
DOI
10.1007/978-3-319-50496-4_9
Links

A Simple, Straightforward and Effective Model for Joint Bilingual Terms Detection and Word Alignment in SMT - scientific work about Wikipedia quality published in 2016, written by Guoping Huang, Jiajun Zhang, Yu Zhou and Chengqing Zong.

Overview

Terms extensively exist in specific domains, and term translation plays a critical role in domain-specific statistical machine translation (SMT) tasks. However, it’s a challenging task to extract term translation knowledge from parallel sentences because of the error propagation in the SMT training pipeline. In this paper, authors propose a simple, straightforward and effective model to mitigate the error propagation and improve the quality of term translation. The proposed model goes from initial weak monolingual detection of terms based on naturally annotated resources (e.g. Wikipedia) to a stronger bilingual joint detection of terms, and allows the word alignment to interact. The extensive experiments show that their method substantially boosts the performance of bilingual term detection by more than 8 points absolute F-score. And the term translation quality is substantially improved by more than 3.66% accuracy, as well as the sentence translation quality is significantly improved by 0.38 absolute BLEU points, compared with the strong baseline, i.e. the well tuned Moses.

Embed

Wikipedia Quality

Huang, Guoping; Zhang, Jiajun; Zhou, Yu; Zong, Chengqing. (2016). "[[A Simple, Straightforward and Effective Model for Joint Bilingual Terms Detection and Word Alignment in SMT]]". Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Volume 10102, 1 December 2016, pp. 103-115. ISSN: 03029743. DOI: 10.1007/978-3-319-50496-4_9.

English Wikipedia

{{cite journal |last1=Huang |first1=Guoping |last2=Zhang |first2=Jiajun |last3=Zhou |first3=Yu |last4=Zong |first4=Chengqing |title=A Simple, Straightforward and Effective Model for Joint Bilingual Terms Detection and Word Alignment in SMT |date=2016 |issn=03029743 |doi=10.1007/978-3-319-50496-4_9 |url=https://wikipediaquality.com/wiki/A_Simple,_Straightforward_and_Effective_Model_for_Joint_Bilingual_Terms_Detection_and_Word_Alignment_in_SMT |journal=Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Volume 10102, 1 December 2016, pp. 103-115}}

HTML

Huang, Guoping; Zhang, Jiajun; Zhou, Yu; Zong, Chengqing. (2016). &quot;<a href="https://wikipediaquality.com/wiki/A_Simple,_Straightforward_and_Effective_Model_for_Joint_Bilingual_Terms_Detection_and_Word_Alignment_in_SMT">A Simple, Straightforward and Effective Model for Joint Bilingual Terms Detection and Word Alignment in SMT</a>&quot;. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Volume 10102, 1 December 2016, pp. 103-115. ISSN: 03029743. DOI: 10.1007/978-3-319-50496-4_9.