Why does an inexperienced translator using statistical machine translation sometimes produce fluent but culturally inappropriate translations, even with a large corpus?

💡 Explanation

Statistical machine translation focuses on fluency based on statistical patterns; however, it often misses cultural nuances, because the model's word embeddings and translation probabilities don't encode pragmatic understanding of cultural context. Therefore, a fluent but inappropriate translation occurs, rather than a semantically accurate but awkward one.

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