A framework of a mechanical translation between Japanese and English by analogy principle
Proc. of the international NATO symposium on Artificial and human intelligence
VENUS: two-phase machine translation system
Future Generation Computer Systems - Special issue on machine translation
A statistical approach to machine translation
Computational Linguistics
Toward memory-based translation
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Towards a Dynamic Linkage of Example-based and Rule-based Machine Translation
Machine Translation
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
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We propose a new method to resolve ambiguity in translation and meaning interpretation using linguistic statistics extracted from dual corpora of source and target languages in addition to the logical restrictions described on dictionary and grammar rules for ambiguity resolution. It provides reasonable criteria for determining a suitable equivalent translation or meaning by making the dependency relation in the source language be reflected in the translated text. The method can be tractable because the required statistics can be computed semi-automatically in advance from a source language corpus and a target language corpus, while an ordinal corpus-based translation method needs a large volume of bilingual corpus of strict pairs of a sentence and its translation. Moreover, it also provides the means to compute the linguistic statistics on the pairs of meaning expressions.