查看文章

The present article introduces a phrasealignment approach that involves the processing of a small bilingual corpus in order to extract suitable structural information. This is used in the PRESEMT project, whose aim is the quick development of phrase-based Machine Translation (MT) systems for new language pairs. A main bottleneck of such systems is the need to create compatible parsing schemes in the source and target languages. This bottleneck is overcome by combining two modules, the Phrase aligner module and the Phrasing model generator, both of them being based on pattern recognition principles.