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Actual exam question for NVIDIA's NCA-GENM exam Question #: 277 Topic #: 1
You are building a system that takes an image of a scene and a short audio clip as input and generates a descriptive text. You want to evaluate the system's performance. Which of the following evaluation metrics are MOST suitable for assessing both the accuracy and the coherence of the generated descriptions in relation to the input image and audio?
BLEU, CIDEr, and SPICE are all suitable for evaluating image captioning and similar generative tasks. BLEU measures the n-gram overlap between the generated text and reference texts. CIDEr specifically focuses on consensus-based image description evaluation, weighting n-grams that are more common among human-generated captions. SPICE focuses on semantic propositional content and captures object, attribute, and relationship triples. ROUGE focuses on recall, but the other 3 provide the best overall picture. Perplexity and WER are more suitable for language models, and Inception Score and FID are used for evaluating the quality of generated images.
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