The Limits of Reference-Free Speech Quality Metrics as Evaluators and Rewards on Modern Text-to-Speech

Reference-free quality predictors such as UTMOS, DNSMOS and SCOREQ are the de facto automatic evaluators for text-to-speech (TTS) and are increasingly adopted as reward signals for preference optimization. Both roles presuppose that the predicted score tracks human preference. In this work, we test this assumption across six human-rated corpora spanning the quality range from artifact-rich to defect-free TTS, evaluating each predictor on a pairwise task that asks whether the clip it scores higher is the clip listeners prefer, and we subject interpretable prosodic and signal-processing features to the same protocol. When one clip carries audible defects the predictors tend to agree with li...

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