Towards a Unified Approach to Memory- and Statistical-Based Machine Translation
UNIVERSITY OF SOUTHERN CALIFORNIA MARINA DEL REY INFORMATION SCIENCES INST
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We present a set of algorithms that enable us to translate natural language sentences by exploiting both a translation memory and a statistical-based translation model. Our results show that an automatically derived translation memory can be used within a statistical framework to often find translations of higher probability than those found using solely a statistical model. The translations produced using both the translation memory and the statistical model are significantly better than translations produced by two commercial systems our hybrid system translated perfectly 58 of the 505 sentences in a test collection, while the commercial systems translated perfectly only 40-42 of them.
- Numerical Mathematics