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Cascaded re-ranking modelling of translation hypotheses using extreme learning machines
Vong, Chi Man1; Liu, Yan1; Cao, Jiuwen2; Yin, Chun3
2017-09
Source PublicationAPPLIED SOFT COMPUTING
ISSN1568-4946
Volume58Pages:681-689
Abstract

In statistical machine translation (SMT), re-ranking of huge amount of randomly generated translation hypotheses is one of the essential components in determining the quality of translation result. In this work, a novel re-ranking modelling framework called cascaded re-ranking modelling (CRM) is proposed by cascading a classification model and a regression model. The proposed CRM effectively and efficiently selects the good but rare hypotheses in order to alleviate simultaneously the issues of translation quality and computational cost. CRM can be partnered with any classifier such as support vector machines (SVM) and extreme learning machine (ELM). Compared to other state-of-the-art methods, experimental results show that CRM partnered with ELM (CRM-ELM) can raise at most 11.6% of translation quality over the popular benchmark Chinese-English corpus (IWSLT 2014) and French-English parallel corpus (WMT 2015) with extremely fast training time for huge corpus. (C) 2017 Elsevier B.V. All rights reserved.

KeywordCascaded Re-ranking Modelling Extreme Learning Machine Statistical Machine Translation
DOI10.1016/j.asoc.2017.05.002
URLView the original
Indexed BySCI ; SSCI ; SSCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000405457500049
PublisherELSEVIER SCIENCE BV
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorVong, Chi Man; Liu, Yan; Cao, Jiuwen; Yin, Chun
Affiliation1.Department of Computer and Information Science, University of Macau, Macau
2.Institute of Information and Control, Hangzhou Dianzi University, Zhejiang 310018, China
3.School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Vong, Chi Man,Liu, Yan,Cao, Jiuwen,et al. Cascaded re-ranking modelling of translation hypotheses using extreme learning machines[J]. APPLIED SOFT COMPUTING,2017,58:681-689.
APA Vong, Chi Man,Liu, Yan,Cao, Jiuwen,&Yin, Chun.(2017).Cascaded re-ranking modelling of translation hypotheses using extreme learning machines.APPLIED SOFT COMPUTING,58,681-689.
MLA Vong, Chi Man,et al."Cascaded re-ranking modelling of translation hypotheses using extreme learning machines".APPLIED SOFT COMPUTING 58(2017):681-689.
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