Zero Shot Speaker Adaptation

Zero-shot speaker adaptation in speech synthesis aims to generate realistic speech in a new speaker's voice using only a short audio sample, without retraining the model. Current research focuses on improving the accuracy and naturalness of synthesized speech, particularly for speakers with accents or limited data, employing techniques like diffusion models, variational autoencoders, and multi-scale acoustic prompts to better capture speaker characteristics. These advancements are significant for applications such as personalized text-to-speech systems and voice cloning, offering potential for more inclusive and versatile speech technologies.