Lexical transfer using a vector-space model

Authors:
Eiichiro Sumita
Affiliations:
ATR Spoken Language Translation Research Laboratories, Soraku, Kyoto, Japan
Venue:
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Year:
2000

Citing 4
Cited 1

Translation using information on dialogue participants

ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Deriving transfer rules from dominance-preserving alignments

COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Toward memory-based translation

COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Learning translation templates from bilingual text

COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2

Base Noun Phrase translation using web data and the EM algorithm

COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1

Quantified Score

Hi-index	0.00

Visualization

Abstract

Building a bilingual dictionary for transfer in a machine translation system is conventionally done by hand and is very time-consuming. In order to overcome this bottleneck, we propose a new mechanism for lexical transfer, which is simple and suitable for learning from bilingual corpora. It exploits a vector-space model developed in information retrieval research. We present a preliminary result from our computational experiment.