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Improving Alignments for Better Confusion Networks for Combining Machine Translation Systems
Necip Fazil Ayan
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Jing Zheng
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Wen Wang
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Paper Details:
Month: August
Year: 2008
Location: Manchester, UK
Venue:
COLING |
Citations
URL
Hybrid Decoding: Decoding with Partial Hypotheses Combination over Multiple SMT Systems
Lei Cui
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Dongdong Zhang
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Mu Li
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Ming Zhou
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Tiejun Zhao
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The Feature Subspace Method for SMT System Combination
Nan Duan
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Mu Li
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Tong Xiao
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Ming Zhou
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Collaborative Decoding: Partial Hypothesis Re-ranking Using Translation Consensus between Decoders
Mu Li
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Nan Duan
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Dongdong Zhang
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Chi-Ho Li
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Ming Zhou
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A Comparative Study of Hypothesis Alignment and its Improvement for Machine Translation System Combination
Boxing Chen
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Min Zhang
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Haizhou Li
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Aiti Aw
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Neural System Combination for Machine Translation
Long Zhou
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Wenpeng Hu
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Jiajun Zhang
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Chengqing Zong
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Incremental Hypothesis Alignment with Flexible Matching for Building Confusion Networks: BBN System Description for WMT09 System Combination Task
Antti-Veikko Rosti
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Bing Zhang
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Spyros Matsoukas
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Richard Schwartz
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Review of Hypothesis Alignment Algorithms for MT System Combination via Confusion Network Decoding
Antti-Veikko Rosti
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Xiaodong He
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Damianos Karakos
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Gregor Leusch
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Yuan Cao
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Markus Freitag
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Spyros Matsoukas
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Hermann Ney
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Jason Smith
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Bing Zhang
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http://creativecommons.org/licenses/by-nc-sa/3.0/
http://wordnet.princeton.edu
Field Of Study
Task
Machine Translation
Spoken Language Processing
Language
Chinese
English
Arabic
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