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» Non-linear Learning for Statistical Machine Translation
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148
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ACL
2010
15 years 1 months ago
cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models
We present cdec, an open source framework for decoding, aligning with, and training a number of statistical machine translation models, including word-based models, phrase-based m...
Chris Dyer, Adam Lopez, Juri Ganitkevitch, Jonatha...
142
Voted
CIKM
2010
Springer
15 years 2 months ago
Clickthrough-based translation models for web search: from word models to phrase models
Web search is challenging partly due to the fact that search queries and Web documents use different language styles and vocabularies. This paper provides a quantitative analysis ...
Jianfeng Gao, Xiaodong He, Jian-Yun Nie
112
Voted
LREC
2010
169views Education» more  LREC 2010»
15 years 5 months ago
Using Comparable Corpora to Adapt a Translation Model to Domains
Statistical machine translation (SMT) requires a large parallel corpus, which is available only for restricted language pairs and domains. To expand the language pairs and domains...
Hiroyuki Kaji, Takashi Tsunakawa, Daisuke Okada
135
Voted
EMNLP
2008
15 years 5 months ago
Phrase Translation Probabilities with ITG Priors and Smoothing as Learning Objective
The conditional phrase translation probabilities constitute the principal components of phrase-based machine translation systems. These probabilities are estimated using a heurist...
Markos Mylonakis, Khalil Sima'an
124
Voted
ICML
1998
IEEE
16 years 4 months ago
Learning a Language-Independent Representation for Terms from a Partially Aligned Corpus
Cross-language latent semantic indexing is a method that learns useful languageindependent vector representations of terms through a statistical analysis of a documentaligned text...
Michael L. Littman, Fan Jiang, Greg A. Keim