We propose an automatic machine translation (MT) evaluation metric that calculates a similarity score (based on precision and recall) of a pair of sentences. Unlike most metrics, ...
We propose three new features for MT evaluation: source-sentence constrained n-gram precision, source-sentence reordering metrics, and discriminative unigram precision, as well as...
The need for automated text evaluation is common to several AI disciplines. In this work, we explore the use of Machine Translation (MT) evaluation metrics for Textual Case Based R...
Ibrahim Adeyanju, Nirmalie Wiratunga, Robert Lothi...
Translating between dissimilar languages requires an account of the use of divergent word orders when expressing the same semantic content. Reordering poses a serious problem for s...
It is recognized that many evaluation metrics of machine translation in use that focus on surface word level suffer from their lack of tolerance of linguistic variance, and the in...