BLEU

BLEU has frequently been reported as correlating well with human judgement,[1][2][3] and remains a benchmark for the assessment of any new evaluation metric. There are however a number of criticisms that have been voiced. It has been noted that although … Read More

BLEU (Bilingual Evaluation Understudy) is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Quality is considered to be the correspondence between a machine’s output and that of a human: “the … Read More

The METEOR metric is designed to address some of the deficiencies inherent in the BLEU metric. The metric is based on the weighted harmonic mean of unigram precision and unigram recall. The metric was designed after research by Lavie (2004) … Read More

The NIST metric is based on the BLEU metric, but with some alterations. Where BLEU simply calculates n-gram precision adding equal weight to each one, NIST also calculates how informative a particular n-gram is. That is to say when a … Read More

BLEU was one of the first metrics to report high correlation with human judgements of quality. The metric is currently one of the most popular in the field. The central idea behind the metric is that “the closer a machine … Read More