Language resource quality is crucial in NLP. Many of the resources used are derived from data created by human beings out of an NLP context, especially regarding MT and reference ...
Translation systems are generally trained to optimize BLEU, but many alternative metrics are available. We explore how optimizing toward various automatic evaluation metrics (BLEU...
Daniel Cer, Christopher D. Manning, Daniel Jurafsk...
We present ParaMetric, an automatic evaluation metric for data-driven approaches to paraphrasing. ParaMetric provides an objective measure of quality using a collection of multipl...
Automatic evaluation metrics are fast and cost-effective measurements of the quality of a Machine Translation (MT) system. However, as humans are the end-user of MT output, human ...
We present the methodology that underlies new metrics for semantic machine translation evaluation that we are developing. Unlike widely-used lexical and n-gram based MT evaluation...