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BLEU (Bilingual Evaluation Understudy) score is a metric used to evaluate the quality of machine translation output by comparing it to one or more reference translations. This guide provides a step-by-step process to calculate BLEU scores effectively.
Understanding BLEU Score
The BLEU score measures how closely a machine-generated translation matches human references. It considers the overlap of n-grams between the candidate and reference translations, along with a brevity penalty to discourage overly short translations.
Step 1: Prepare Data
Gather the candidate translation and one or more reference translations. Ensure all texts are tokenized consistently, splitting sentences into words or subword units.
Step 2: Calculate N-gram Precision
For each n-gram size (commonly 1 to 4), count the number of n-grams in the candidate translation that also appear in the reference translations. Divide this count by the total number of n-grams in the candidate to obtain precision scores for each n-gram level.
Step 3: Apply Brevity Penalty
The brevity penalty (BP) penalizes translations that are shorter than the reference. Calculate it as:
BP = 1 if candidate length > reference length; otherwise, BP = e^{(1 – reference length / candidate length)}.
Step 4: Compute Final BLEU Score
Combine the n-gram precisions using geometric mean and multiply by the brevity penalty:
BLEU = BP * exp(average of log precisions for n=1 to 4).
Additional Tips
- Use multiple reference translations for better evaluation.
- Ensure consistent tokenization across all texts.
- Utilize existing tools or libraries for calculation, such as NLTK or SacreBLEU.