NDLI: Bilingual Continuous-Space Language Model Growing for Statistical Machine Translation

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IEEE Signal Processing Society Information

Year : 2014 Volume : 22

Bilingual Continuous-Space Language Model Growing for Statistical Machine Translation

Content Provider	IEEE Xplore Digital Library
Author	Rui Wang Hai Zhao Bao-Liang Lu Utiyama, M. Sumita, E.
Copyright Year	2014
Abstract	Larger n-gram language models (LMs) perform better in statistical machine translation (SMT). However, the existing approaches have two main drawbacks for constructing larger LMs: 1) it is not convenient to obtain larger corpora in the same domain as the bilingual parallel corpora in SMT; 2) most of the previous studies focus on monolingual information from the target corpora only, and redundant n-grams have not been fully utilized in SMT. Nowadays, continuous-space language model (CSLM), especially neural network language model (NNLM), has been shown great improvement in the estimation accuracies of the probabilities for predicting the target words. However, most of these CSLM and NNLM approaches still consider monolingual information only or require additional corpus. In this paper, we propose a novel neural network based bilingual LM growing method. Compared to the existing approaches, the proposed method enables us to use bilingual parallel corpus for LM growing in SMT. The results show that our new method outperforms the existing approaches on both SMT performance and computational efficiency significantly.
Starting Page	1209
Ending Page	1220
Page Count	12
File Size	1772514
File Format	PDF
ISSN	23299290
Volume Number	23
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Joining processes Probability Decoding Training IEEE transactions Speech Speech processing statistical machine translation (SMT) Continuous-space language model language model growing (LMG) neural network language model
Content Type	Text
Resource Type	Article
Subject	Acoustics and Ultrasonics Signal Processing Instrumentation Speech and Hearing Electrical and Electronic Engineering Computational Mathematics Media Technology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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