Models of Translational Equivalence among Words

Models of Translational Equivalence among Words (2000)

by I. Dan Melamed

Venue:	Computational Linguistics
Citations:	121 - 2 self

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Datum	Value	Source
TITLE	Models of Translational Equivalence among Words	user correction - Legacy Corrections
AUTHOR NAME	I. Dan Melamed	SVM HeaderParse 0.1
AUTHOR AFFIL	West Group	SVM HeaderParse 0.2
ABSTRACT	This article presents methods for biasing statistical translation models to reflect these properties. Evaluation with respect to independent human judgments has confirmed that translation models biased in this fashion are significantly more accurate than a baseline knowledge-free model. This article also shows how a statistical translation model can take advantage of preexisting knowledge that might be available about particular language pairs. Even the simplest kinds of languagespecific knowledge, such as the distinction between content words and function words, are shown to reliably boost translation model performance on some tasks. Statistical models that reflect knowledge about the model domain combine the best of both the rationalist and empiricist paradigms	user correction - Legacy Corrections
YEAR	2000	INFERENCE
VENUE	Computational Linguistics	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	221--249	INFERENCE
VOLUME	26	INFERENCE
CITATIONS	45 found	ParsCit 1.0