Learning translation templates from examples
Information Systems - Special issue on selected papers from 6th annual workshop on information technologies and systems, December 1996, Cleveland, Ohio, USA
Learning Translation Templates from Bilingual Translation Examples
Applied Intelligence
Corpus-Based Learning of Generalized parse Tree Rules for Translation
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Example-Based Machine Translation via the Web
AMTA '02 Proceedings of the 5th Conference of the Association for Machine Translation in the Americas on Machine Translation: From Research to Real Users
Computational Linguistics - Special issue on web as corpus
Translation using information on dialogue participants
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Automated generalization of translation examples
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
From COGRAM to ALCOGRAM: toward a controlled English grammar checker
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Cooperation between transfer and analysis in example-based framework
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Learning translation templates from bilingual text
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
The KANT system: fast, accurate, high-quality translation in practical domains
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 3
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Recent Advances in Example-Based Machine Translation
Computational Linguistics
The LRC machine translation system
Computational Linguistics - Special issue on machine translation
ORANGE: a method for evaluating automatic evaluation metrics for machine translation
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Significance tests of automatic machine translation evaluation metrics
Machine Translation
Panning for EBMT gold, or "Remembering not to forget"
Machine Translation
| Hi-index | 0.00 |
This paper presents an extended, harmonised account of our previous work on integrating controlled language data in an Example-based Machine Translation system. Gough and Way in MT Summit pp. 133---140 (2003) focused on controlling the output text in a novel manner, while Gough and Way (9th Workshop of the EAMT, (2004a), pp. 73---81) sought to constrain the input strings according to controlled language specifications. Our original sub-sentential alignment algorithm could deal only with 1:1 matches, but subsequent refinements enabled n:m alignments to be captured. A direct consequence was that we were able to populate the system's databases with more than six times as many potentially useful fragments. Together with two simple novel improvements --- correcting a small number of mistranslations in the lexicon, and allowing multiple translations in the lexicon --- translation quality improves considerably. We provide detailed automatic and human evaluations of a number of experiments carried out to test the quality of the system. We observe that our system outperforms the rule-based on-line system Logomedia on a range of automatic evaluation metrics, and that the `best' translation candidate is consistently highly ranked by our system. Finally, we note in a number of tests that the BLEU metric gives objectively different results than other automatic evaluation metrics and a manual evaluation. Despite these conflicting results, we observe a preference for controlling the source data rather than the target translations.