BLEU (Bilingual Evaluation Understudy)
An evaluation metric that measures the quality of machine-translated text by comparing it with one or more human-generated reference translations.
What is BLEU?
BLEU evaluates generated text by measuring how closely its words and short word sequences match those in reference outputs. It was originally developed for machine translation but can also be applied to other text-generation tasks. BLEU typically produces a score indicating the level of similarity between the generated output and the reference, with higher scores generally representing closer matches.
Why is BLEU Important?
BLEU provides a standardized and automated way to evaluate generated text without requiring humans to review every output. It enables researchers and developers to compare different models and track improvements. However, BLEU does not fully capture meaning, fluency, or overall response quality.
Common use cases
BLEU is commonly used for evaluating machine translation, text generation, language models, and other natural language processing systems.