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» Non-linear Learning for Statistical Machine Translation
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ACL
2010
14 years 11 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...
CIKM
2010
Springer
14 years 11 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
LREC
2010
169views Education» more  LREC 2010»
15 years 2 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
EMNLP
2008
15 years 2 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
ICML
1998
IEEE
16 years 1 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