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This work proposes repurposing XTTSv2, a multilingual voice cloning model trained on 27k hours of speech, for speaker anonymization without retraining, and introduces an iterative refinement strategy that balances privacy and utility by maximizing a harmonic mean of speaker dissimilarity and intelligibility.
A Bayesian evaluation framework is introduced that jointly models retrieval success, abstention behavior, and answer correctness, factorized according to the pipeline's information flow, and extends to incorporate LLM-as-a-judge annotations as calibrated noisy observations, enabling practitioners to combine limited hum...
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