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Neural probabilistic language model for system combination

Okita, Tsuyoshi (2012) Neural probabilistic language model for system combination. In: ML4HMT-12 Workshop, 9 Dec 2012, Mumbai, India.

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Abstract

This paper gives the system description of the neural probabilistic language modeling (NPLM) team of Dublin City University for our participation in the system combination task in the Second Workshop on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid MT (ML4HMT-12). We used the information obtained by NPLM as meta information to the system combination module. For the Spanish-English data, our paraphrasing approach achieved 25.81 BLEU points, which lost 0.19 BLEU points absolute compared to the standard confusion network-based system combination. We note that our current usage of NPLM is very limited due to the difficulty in combining NPLM and system combination.

Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:No
Uncontrolled Keywords:statistical machine translation; neural probabilistic language model; system combination
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:17683
Deposited On:20 Dec 2012 10:45 by Tsuyoshi Okita . Last Modified 19 Jul 2018 14:58

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