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» Learning Rules to Improve a Machine Translation System
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EMNLP
2010
14 years 9 months ago
Hierarchical Phrase-Based Translation Grammars Extracted from Alignment Posterior Probabilities
We report on investigations into hierarchical phrase-based translation grammars based on rules extracted from posterior distributions over alignments of the parallel text. Rather ...
Adrià de Gispert, Juan Pino, William J. Byr...
COLING
2010
14 years 6 months ago
Learning Phrase Boundaries for Hierarchical Phrase-based Translation
Hierarchical phrase-based models provide a powerful mechanism to capture non-local phrase reorderings for statistical machine translation (SMT). However, many phrase reorderings a...
Zhongjun He, Yao Meng, Hao Yu
NAACL
2007
15 years 1 months ago
A Log-Linear Block Transliteration Model based on Bi-Stream HMMs
We propose a novel HMM-based framework to accurately transliterate unseen named entities. The framework leverages features in letteralignment and letter n-gram pairs learned from ...
Bing Zhao, Nguyen Bach, Ian R. Lane, Stephan Vogel
AIPS
2003
15 years 1 months ago
Learning Rules for Adaptive Planning
This paper presents a novel idea, which combines Planning, Machine Learning and Knowledge-Based techniques. It is concerned with the development of an adaptive planning system tha...
Dimitris Vrakas, Grigorios Tsoumakas, Nick Bassili...
ICASSP
2010
IEEE
15 years 38 min ago
Automatic disfluency removal for improving spoken language translation
Statistical machine translation (SMT) systems for spoken languages suffer from conversational speech phenomena, in particular, the presence of speech dis uencies. We examine the i...
Wen Wang, Gökhan Tür, Jing Zheng, Necip ...