<h2>BLEU</h2>
<p>Bilingual evaluation understudy (or BLEU) is a metric for evaluating the quality of machine translation using human translation as examples of acceptable quality results.  This metric has become a widely used standard in the research literature.  But is it the perfect measure of quality of machine translation?  This episode explores that idea.</p>
<h3>Related Links</h3>
<ul>
<li><a href="http://www.cis.upenn.edu/~ccb/">Chris Callison-Burch</a></li>
<li><a href="https://twitter.com/ccb">Chris on Twitter</a></li>
<li><a href="http://www.statmt.org/moses/">Moses</a></li>
<li><a href="http://aclweb.org/anthology/P/P02/P02-1040.pdf">BLEU: a Method for Automatic Evaluation of Machine Translation</a> </li>
<li><a href="http://www.cs.jhu.edu/~ccb/publications/re-evaluating-the-role-of-bleu-in-mt-research.pdf">Re-evaluating the Role of BLEU in Machine Translation Research</a></li>
<li><a href="http://www.statmt.org/wmt19/">ACL 2019, Fourth conference on machine translation (WMT19)</a></li>
</ul>