The present article introduces a phrase-alignment approach that involves the processing of a small bilingual corpus in order to extract suitable structural infor-mation. This is used in the PRESEMT project, whose aim is the quick develop-ment of phrase-based Machine Transla-tion (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 lan-guages. 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.