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Synthetic voices can now achieve remarkable acoustic accuracy, yet often fail to sound “natural,” especially when designed to reproduce one's own voice. Existing frameworks define naturalness along two dimensions: deviation from acoustic norms and human-likeness. Yet these dimensions overlook the self-voice, which can feel natural or unnatural for reasons beyond the signal itself. Here, self-relevance is proposed as a complementary dimension, capturing the subjective alignment between a voice and the listener's self-representation. Evidence shows that self-relevance modulates perceived naturalness independently of acoustic match. A full understanding of voice naturalness, therefore, requires integrating physical speech properties with the listener's self-representational framework.
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Ana P. Pinheiro (2025) studied this question.
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