MEANT

We introduce a novel semi-automated metric, MEANT, that assesses translation utility by match- ing semantic role fillers, producing scores that cor- relate with human judgment as well as HTER but …...

We present larger-scale evidence overturning pre- vious results, showing that among the many al- ternative phrasal lexical similarity measures based on word vectors, the Jaccard coefficient most in- creases the …...

We introduce the first fully automatic, fully seman- tic frame based MT evaluation metric, MEANT, that outperforms all other commonly used auto- matic metrics in correlating with human judgment on …...

The linguistically transparent MEANT and UMEANT metrics are tunable, simple yet highly effective, fully automatic ap- proximation to the human HMEANT MT evaluation metric which measures seman- tic frame similarity …...

We show that applying semantic role label constraints to bracketing ITG alignment to train MT systems improves the quality of MT output in comparison to the conventional BITG and GIZA …...

AbstractPrevious attempts at injecting semantic frame biases into SMT training for low resource languages failed because either (a) no semantic parser is available for the low resource input language; or …...