Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 79 discussion

Métrica Uso Principal BLEU ✅ Tradução de texto (Machine Translation) ROUGE Resumo de texto (Text Summarization) RMSE Modelos de regressão F1 Score Classificação

BLEU (Bilingual Evaluation Understudy) score is a metric specifically designed for evaluating the quality of machine-generated translations by comparing them to one or more human-produced reference translations. BLEU is particularly useful for measuring the accuracy of translations, which is exactly what the company needs to evaluate in this scenario.

A. Bilingual Evaluation Understudy (BLEU): This is the correct answer. BLEU is a common metric for evaluating machine translation quality. It compares the generated text to one or more reference translations and measures the n-gram overlap.

The correct answer is A. BLEU is specifically designed to evaluate machine translation quality.

BLEU is specifically designed to measure the quality of machine translations by comparing them to human-created reference translations

C. Recall-Oriented Understudy for Gisting Evaluation (ROUGE) ROUGE is a popular metric for evaluating the quality of text summarization and machine translation systems. It focuses on recall, measuring how well the generated text covers the relevant information from the reference text. In this case, ROUGE can be used to assess how accurately the LLM-generated translations capture the meaning and content of the original English manuals.

BLEU (bilingual evaluation understudy) is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another.