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Training Continuous Space Language Models: Some Practical Issues
Hai Son Le
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Alexandre Allauzen
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Guillaume Wisniewski
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François Yvon
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Paper Details:
Month: October
Year: 2010
Location: Cambridge, MA
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Converting Continuous-Space Language Models into N-Gram Language Models for Statistical Machine Translation
Rui Wang
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Masao Utiyama
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Isao Goto
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Eiichro Sumita
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Hai Zhao
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Bao-Liang Lu
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Neural Network Based Bilingual Language Model Growing for Statistical Machine Translation
Rui Wang
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Hai Zhao
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Bao-Liang Lu
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Masao Utiyama
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Eiichiro Sumita
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Learning Better Embeddings for Rare Words Using Distributional Representations
Irina Sergienya
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Hinrich Schütze
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Large, Pruned or Continuous Space Language Models on a GPU for Statistical Machine Translation
Holger Schwenk
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Anthony Rousseau
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Mohammed Attik
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English to Chinese Translation: How Chinese Character Matters
Rui Wang
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Hai Zhao
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Bao-Liang Lu
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Neural Network Language Model for Chinese Pinyin Input Method Engine
Shenyuan Chen
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Hai Zhao
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Rui Wang
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A Machine Learning Method to Distinguish Machine Translation from Human Translation
Yitong Li
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Rui Wang
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Hai Zhao
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http://www.itl.nist.gov/iad/mig/tests/
Field Of Study
Linguistic Trends
Embeddings
Task
Machine Translation
Approach
Deep Learning
Language
English
French
Arabic
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