A framework of a mechanical translation between Japanese and English by analogy principle
Proc. of the international NATO symposium on Artificial and human intelligence
The connection machine
Communications of the ACM - Special issue on parallelism
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
Inside Case-Based Reasoning
Experiments and prospects of Example-Based Machine Translation
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Toward memory-based translation
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Massively parallel memory-based parsing
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
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This paper reports experimental results of a high performance (real-time) memory-based translation. Memory-based translation is a new approach to machine translation which uses examples, or cases, of past translations to carry out translation of sentences. This idea is counter to traditional machine translation systems which rely on extensive use of rules in parsing, transfer and generation. Although, there are some preliminary reports on the superiority of the memory-based translation in terms of its scalability, quality of translation, and easiness of grammar writing, we have not seen any reports on its performance. This is perhaps, the first report discussing the feasibility and problems of the approach based on actual massively parallel implementation using real data. We also claim that the architecture of the IXM2 associative processor is highly suitable for memory-based translation tasks. Parsing performance of the memory-based translation system attained a few milliseconds per sentence.