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» Cognates Can Improve Statistical Translation Models
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ACL
2006
15 years 1 months ago
Modelling Lexical Redundancy for Machine Translation
Certain distinctions made in the lexicon of one language may be redundant when translating into another language. We quantify redundancy among source types by the similarity of th...
David Talbot, Miles Osborne
ICMLA
2009
14 years 9 months ago
Improving Clinical Relevance in Ensemble Support Vector Machine Models of Radiation Pneumonitis Risk
Patients undergoing thoracic radiation therapy can develop radiation pneumonitis (RP), a potentially fatal inflammation of the lungs. Support vector machines (SVMs), a statistical...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...
COLING
2010
14 years 6 months ago
Unsupervised Part of Speech Tagging Using Unambiguous Substitutes from a Statistical Language Model
We show that unsupervised part of speech tagging performance can be significantly improved using likely substitutes for target words given by a statistical language model. We choo...
Mehmet Ali Yatbaz, Deniz Yuret
INTERSPEECH
2010
14 years 6 months ago
Combining many alignments for speech to speech translation
Alignment combination (symmetrization) has been shown to be useful for improving Machine Translation (MT) models. Most existing alignment combination techniques are based on heuri...
Sameer Maskey, Steven J. Rennie, Bowen Zhou
NIPS
2007
15 years 1 months ago
HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation
We present a novel paradigm for statistical machine translation (SMT), based on a joint modeling of word alignment and the topical aspects underlying bilingual document-pairs, via...
Bing Zhao, Eric P. Xing