Modular MT with a learned bilingual dictionary: rapid deployment of a new language pair

Authors:
Jessie Pinkham;Martine Smets
Affiliations:
Microsoft Research, Redmond, WA;Microsoft Research, Redmond, WA
Venue:
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Year:
2002

Citing 3
Cited 1

Overcoming the customization bottleneck using example-based MT

DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
A best-first alignment algorithm for automatic extraction of transfer mappings from bilingual corpora

DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Towards a simple and accurate statistical approach to learning translation relationships among words

DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14

METIS-II: low resource machine translation

Machine Translation

Quantified Score

Hi-index	0.00

Visualization

Abstract

The MT system described in this paper combines hand-built analysis and generation components with automatically learned example-based transfer patterns. Up to now, the transfer component used a traditional bilingual dictionary to seed the transfer pattern learning process and to provide fallback translations at runtime. This paper describes an improvement to the system by which the bilingual dictionary used for these purposes is instead learned automatically from aligned bilingual corpora, making the system's transfer knowledge entirely derivable from corpora. We show that this system with a fully automated transfer process performs better than the system with a hand-crafted bilingual dictionary. More importantly, this has enabled us to create in less than one day a new language pair, French-Spanish, which, for a technical domain, surpasses the quality bar of the commercial system chosen for comparison.