Cascaded Re-ranking Modelling of Translation Hypotheses using Extreme Learning Machines

UM > Faculty of Science and Technology > DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE

Status	已發表Published
	Cascaded Re-ranking Modelling of Translation Hypotheses using Extreme Learning Machines
	Vong, C. M.; Liu, Y.; Cao, J.W.; Yin, C.
	2017-09-01
Source Publication	Applied Soft Computing (SCI-E)
ISSN	1568-4946
Pages	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 \textit{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 \textit{support vector machines} (SVM) and \textit{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.
Keyword	Cascaded Re-ranking Modelling Extreme Learning Machine Statistical Machine Translation
Language	英語English
The Source to Article	PB_Publication
PUB ID	28905
Document Type	Journal article
Collection	DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding Author	Vong, C. M.
Recommended Citation GB/T 7714	Vong, C. M.,Liu, Y.,Cao, J.W.,et al. Cascaded Re-ranking Modelling of Translation Hypotheses using Extreme Learning Machines[J]. Applied Soft Computing (SCI-E), 2017, 681-689.
APA	Vong, C. M.., Liu, Y.., Cao, J.W.., & Yin, C. (2017). Cascaded Re-ranking Modelling of Translation Hypotheses using Extreme Learning Machines. Applied Soft Computing (SCI-E), 681-689.
MLA	Vong, C. M.,et al."Cascaded Re-ranking Modelling of Translation Hypotheses using Extreme Learning Machines".Applied Soft Computing (SCI-E) (2017):681-689.

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