Abstract

This seminar will be devoted to an overview of the experience in statistical machine translation at UPC during recent years. Firstly, the Ngram-based SMT system will be described, detailing bilingual unit definition and basic feature functions for a monotone language pair. Secondly, the introduction of linguistic information at various stages will be discussed, including word alignment (investigating correlation between Alignment Error Rate and translation scores), bilingual unit segmentation and direct translation modelling. Results on English-to-Spanish verb form classification will be reviewed, as well as the impact of morphology reduction on bilingual N-gram formulation. For language pairs exhibiting less monotone word order, the reordering strategies implemented will be presented. Particularly, reordered search involving tuple unfolding and extended monotone search by linguistically-driven reordering rules will be compared for Arabic, Chinese and Spanish-to-English tasks. Finally, the seminar will conclude outlining general future research directions towards improving performance of current state-of-the-art SMT systems.