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Example-Based Machine Translation of Short Phrases Using the Context Equivalence Principle

By Konstantin Tretyakov


In this paper we consider machine translation in a very specific setting of computerassisted software localization. This setting imposes certain requirements on the kind of translation assistance expected from the computer, and we believe that simple examplebased techniques suit best for the task. We propose a very simplistic method, that exploits the assumption of context-equivalence common to other example-based techniques. The novelty of the approach (as we believe) lies in the fact that it uses no other linguistic heuristics such as word-wise alignments. As a result, the method produces very reliable translations at the price of not being able to translate all sentences – the behaviour that is well-suited for the task at hand. We have tested the method on a realistic dataset of localized messages and labels from a typical web-application, as well as a dataset of messages from KDE games. In different tests the method succeeded in perfectly translating between 5 and 37 percent of the messages with a negligible amount of mistakes. We find this result quite successful.

Year: 2011
OAI identifier: oai:CiteSeerX.psu:
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