Review:
Bleu Score (for Machine Translation)
overall review score: 4
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score is between 0 and 5
The BLEU score (Bilingual Evaluation Understudy) is a widely used automated metric for evaluating the quality of machine translation systems. It measures the correspondence between a machine-generated translation and one or more reference translations by computing n-gram overlaps, providing an objective assessment of translation accuracy and fluency.
Key Features
- Uses n-gram matching to compare candidate and reference translations
- Provides a score between 0 and 1 (often scaled to 0-100) indicating translation quality
- Accounts for precision of overlapping n-grams with meaningful length penalties (brevity penalty)
- Relatively fast and straightforward to compute
- Widely adopted in research and development for machine translation performance benchmarking
Pros
- Automates evaluation, reducing reliance on costly human assessments
- Simple to implement and interpret
- Provides consistent, comparable scores across different systems
- Useful for quick iteration during model development
Cons
- Does not account for semantic adequacy or fluency beyond n-gram overlap
- Sensitive to the choice of reference translations; multiple references improve reliability but are not always available
- Can be gamed by overly conservative translations that match reference wording but lack naturalness
- Less effective at evaluating language pairs with high lexical variability