Artificial Intelligence #zero-shot#tts
ZeSTA Framework Enhances Zero-Shot TTS Augmentation for Data-Efficient Personalized Speech Synthesis
Researchers propose ZeSTA, a domain-conditioned training framework that distinguishes real and synthetic speech via a lightweight domain embedding, combined with real-data oversampling. The approach improves speaker similarity over naive synthetic augmentation while preserving intelligibility and perceptual quality in low-resource personalized speech synthesis.
Jun 20, 2026 1 source