Abstract: We present experiments in using discourse structure for improving machine translation evaluation. We first design two discourse-aware similarity measures, which use all-subtree kernels to compare discourse parse trees in accordance with the Rhetorical Structure Theory. Then, we show that these measures can help improve a number of existing machine translation evaluation metrics both at the segment- and at the system-level. Rather than proposing a single new metric, we show that discourse information is complementary to the state-of-the-art eval...
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Topics: 
Natural language processing
Artificial intelligence