We describe an approach to improve Statistical Machine Translation (SMT) performance using multi-lingual, parallel, sentence-aligned corpora in several bridge languages. Our appro...
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
Using multi-layer neural networks to estimate the probabilities of word sequences is a promising research area in statistical language modeling, with applications in speech recogn...
Hai Son Le, Alexandre Allauzen, Guillaume Wisniews...
This paper describes our first participation in the Indian language sub-task of the main Adhoc monolingual and bilingual track in CLEF1 competition. In this track, the task is to...
We present a machine learning approach to evaluating the wellformedness of output of a machine translation system, using classifiers that learn to distinguish human reference tran...
Simon Corston-Oliver, Michael Gamon, Chris Brocket...