Augmenting a Statistical Translation System with a Translation Memory

In this paper, we present a translation memory (TM) based system to augment a statistical translation (SMT) system. It is used for translating sentences which have close matches in the training corpus. Given a test sentence, we first extract sentence pairs from the training corpus, whose source side is similar to the test sentence. Then, the TM system modifies the translation of the sentences by a sequence of substitution, deletion and insertion operations, to obtain the desired result. Statistical phrase alignment model of the SMT system is used for this purpose. The system was evaluated using a corpus of Chinese-English conversational data. For close matching sentences, the translations produced by the translation memory approach were compared with the translations of the statistical decoder.