We present a human-feedback-based evaluation pipeline for deep learning generative models, tested on music composition. Leveraging Bayesian Optimization and asking users to grade the generated songs, we efficiently find the point of a given model’s latent space that yields each volunteer’s favorite without retraining.
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Gil et al. (2024) studied this question.
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