Using Collocations to Assess MT Quality
Benjamin Han, Alon Lavie · 2005
Conventional metrics for Machine Translation evaluation have focused on using n-gram similarity between a reference translation and a system translation as an indication of the system quality. A simple n-gram model however cannot capture long-distance dependency, and the requirement of a reference translation has prevented the use of these metrics at the decoding stage. In this paper we propose a set of collocation-based metrics to address these problems.