MT Goes Farming: Comparing Two Machine Translation Approaches on a New Domain
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC 2004)
Abstract
In the paper we present detailed analyses of two machine translation systems when applied to documents of a previously unseen domain: agricultural texts from the European Union. The two systems compared are a statistical machine translation (SMT) system using the freely available ISI ReWrite Decoder, and the rule-based machine translation system MATS. For the purpose of comparison we use a sentence-aligned Swedish-English corpus of approximately 75,000 words per language, where 90\% are used for training and 10% are used for evaluation. In the paper we discuss the outcome of automatic evaluation and the results of our manual quality assessment.