Re-assessing the Impact of SMT Techniques with Human Evaluation: a Case Study on English - Croatian

Antonio Toral, Raphael Rubino, Gema Ramírez-Sánchez
2016 European Association for Machine Translation Conferences/Workshops  
We re-assess the impact brought by a set of widely-used SMT models and techniques by means of human evaluation. These include different types of development sets (crowdsourced vs translated professionally), reordering, operation sequence and bilingual neural language models as well as common approaches to data selection and combination. In some cases our results corroborate previous findings found in the literature, when those approaches were evaluated in terms of automatic metrics, but in some other cases they do not.
dblp:conf/eamt/ToralRR16 fatcat:fw7fxliw3vc7njsfrk3yeipeci