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The BLEU Score (Bilingual Evaluation Understudy) evaluates the quality of machine-translated text by comparing a candidate texts translation to one or more reference translations.
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The closer the BLEU score is to one, the better your model is. The closer to zero, the worse it is.
3.To get a BLEU score, the candidates and the references are usually based on an average of uni, bi, try or even four-gram precision.
- BLEU doesn't consider the semantic meaning of words.
- BLUE doesn't consider the sentence structure of the sentence.
- ROGUE stands for Recall Oriented Understudy for Gisting Evaluation, which is a mouthful. But let's you know right off the bat that it's more recall-oriented by default. This means that it's placing more importance on how much of the human created reference appears in the machine translation.
- It was orignially developed to evaluate text-summarization models but works well for NMT as well.
- ROGUE score calculates the precision and recall between the generated text and human-created text.
- Low ROUGUE score doesn't necessarily mean that translation is bad.