Can BLEU replace human evaluation?
BLEU cannot fully replace human evaluation in machine translation quality assessment. As an automated metric, it measures n-gram overlap between a machine-generated output and human reference translations but inherently lacks human-like linguistic understanding.
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BLEU focuses on surface-level lexical similarity, ignoring crucial aspects like semantic accuracy, fluency, coherence, and appropriateness for context. It requires high-quality, multiple reference translations for reliability and is sensitive to the specific domain. Its scores need careful interpretation relative to baseline systems and human judgments, as correlations can vary significantly.
BLEU provides valuable efficiency for rapid system iteration during development and offers an initial, objective benchmark comparison between models, especially at scale. It offers a useful supplement but not a substitute for comprehensive human evaluation, which captures nuanced linguistic quality and pragmatic effectiveness far beyond n-grams. Human judgment remains the ultimate standard for assessing overall translation quality.
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