A path-based transfer model for machine translation

A path-based transfer model for machine translation (2004)

by Dekang Lin

Venue:	In Proceedings of the 20th COLING
Citations:	12 - 0 self

Datum	Value	Source
TITLE	A path-based transfer model for machine translation	INFERENCE
AUTHOR NAME	Dekang Lin	SVM HeaderParse 0.2
AUTHOR AFFIL	Department of Computing Science; University of Alberta	SVM HeaderParse 0.2
AUTHOR ADDR	Edmonton, Alberta, Canada	SVM HeaderParse 0.2
ABSTRACT	We propose a path-based transfer model for machine translation. The model is trained with a word-aligned parallel corpus where the source language sentences are parsed. The training algorithm extracts a set of transfer rules and their probabilities from the training corpus. A rule translates a path in the source language dependency tree into a fragment in the target dependency tree. The problem of finding the most probable translation becomes a graph-theoretic problem of finding the minimum path covering of the source language dependency tree. 1	SVM HeaderParse 0.2
YEAR	2004	INFERENCE
VENUE	In Proceedings of the 20th COLING	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	625--630	INFERENCE
CITATIONS	14 found	ParsCit 1.0