A maximum entropy word aligner for Arabic-English machine translation

A maximum entropy word aligner for Arabic-English machine translation (2005)

by Abraham Ittycheriah , Salim Roukos

Venue:	In Proceedings of HLT-EMNLP
Citations:	47 - 3 self

Datum	Value	Source
TITLE	A maximum entropy word aligner for Arabic-English machine translation	INFERENCE
AUTHOR NAME	Abraham Ittycheriah	SVM HeaderParse 0.2
AUTHOR AFFIL	IBM T.J. Watson Research Center	SVM HeaderParse 0.2
AUTHOR ADDR	1101 Kitchawan Road; Yorktown Heights, NY 10598	SVM HeaderParse 0.2
AUTHOR NAME	Salim Roukos	SVM HeaderParse 0.2
AUTHOR AFFIL	IBM T.J. Watson Research Center	SVM HeaderParse 0.2
AUTHOR ADDR	1101 Kitchawan Road; Yorktown Heights, NY 10598	SVM HeaderParse 0.2
ABSTRACT	This paper presents a maximum entropy word alignment algorithm for Arabic-English based on supervised training data. We demonstrate that it is feasible to create training material for problems in machine translation and that a mixture of supervised and unsupervised methods yields superior performance. The probabilistic model used in the alignment directly models the link decisions. Significant improvement over traditional word alignment techniques is shown as well as improvement on several machine translation tests. Performance of the algorithm is contrasted with human annotation performance. 1	SVM HeaderParse 0.2
YEAR	2005	INFERENCE
VENUE	In Proceedings of HLT-EMNLP	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	89--96	INFERENCE
CITATIONS	15 found	ParsCit 1.0