Extreme Learning Machine for Huge Hypotheses Re-ranking in Statistical Machine Translation

UM > Faculty of Science and Technology

Status	已發表Published
	Extreme Learning Machine for Huge Hypotheses Re-ranking in Statistical Machine Translation
	Liu, Y.; Vong, C. M.; Wong, P. K.
	2017-03-01
Source Publication	Cognitive Computation (SCI-E)
ISSN	1866-9956
Pages	285-294
Abstract	In statistical machine translation (SMT), a possibly infinite number of translation hypotheses can be decoded from a source sentence, among which re-ranking is applied to sort out the best translation result. Undoubtedly, re-ranking is an essential component of SMT for effective and efficient translation. A novel re-ranking method called Scaled Sorted Classification Re-ranking (SSCR) based on extreme learning machine (ELM) classification and minimum error rate training (MERT) is proposed. SSCR contains four steps: (1) the input features are normalized to the range of 0 to 1; (2) an ELM classification model is constructed for hypothesis ranking; (3) each translation hypothesis is ranked using the ELM classification model; and (4) the highest ranked subset of hypotheses are selected, in which the hypothesis with best predicted score based on MERT (system score) is returned as the final translation result. Compared with the baseline score (lower bound), SSCR with ELM classification can raise the translation quality up to 6.7% in IWSLT 2014 Chinese to English corpus. Compared with the state-of-the-art rank boosting, SSCR has a relatively 7.8% of improvement on BLEU in a larger WMT 2015 English-to-French corpus. Moreover, the training time of the proposed method is about 160 times faster than traditional regression-based re-ranking.
Keyword	Re-ranking Extreme learning machine Scaled sorted classification re-ranking Statistical machine
Language	英語English
The Source to Article	PB_Publication
PUB ID	28744
Document Type	Journal article
Collection	Faculty of Science and Technology
Corresponding Author	Vong, C. M.
Recommended Citation GB/T 7714	Liu, Y.,Vong, C. M.,Wong, P. K.. Extreme Learning Machine for Huge Hypotheses Re-ranking in Statistical Machine Translation[J]. Cognitive Computation (SCI-E), 2017, 285-294.
APA	Liu, Y.., Vong, C. M.., & Wong, P. K. (2017). Extreme Learning Machine for Huge Hypotheses Re-ranking in Statistical Machine Translation. Cognitive Computation (SCI-E), 285-294.
MLA	Liu, Y.,et al."Extreme Learning Machine for Huge Hypotheses Re-ranking in Statistical Machine Translation".Cognitive Computation (SCI-E) (2017):285-294.

Files in This Item:
There are no files associated with this item.

If you have any objections to this item, please fill out the form below and the administrator will contact you as soon as possible.
Content:
Email：	*
Affiliation No.
Verification Code:	Refresh

Any comments and suggestions are welcomed.
Title:	*
Content:
Email：	*
Verification Code:	Refresh