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ACL
1998
13 years 8 months ago
Automatic Acquisition of Language Model based on Head-Dependent Relation between Words
Language modeling is to associate a sequence of words with a priori probability, which is a key part of many natural language applications such as speech recognition and statistic...
Seungmi Lee, Key-Sun Choi
EMNLP
2008
13 years 8 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

Book
778views
15 years 4 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
IJCNLP
2005
Springer
14 years 6 days ago
Empirical Study of Utilizing Morph-Syntactic Information in SMT
In this paper, we present an empirical study that utilizes morph-syntactical information to improve translation quality. With three kinds of language pairs matched according to mor...
Young-Sook Hwang, Taro Watanabe, Yutaka Sasaki
ACL
2006
13 years 8 months ago
Improved Discriminative Bilingual Word Alignment
For many years, statistical machine translation relied on generative models to provide bilingual word alignments. In 2005, several independent efforts showed that discriminative m...
Robert C. Moore, Wen-tau Yih, Andreas Bode