Adaptive Text to Speech

Adaptive text-to-speech (TTS) aims to generate synthetic speech that accurately reflects a target speaker's voice characteristics, even with limited training data. Current research focuses on improving the generalization ability of models, particularly for speakers with accents, using techniques like diffusion models and transformer networks, often incorporating both zero-shot and few-shot adaptation strategies. This field is significant because it promises more natural and personalized speech synthesis across diverse populations, impacting applications ranging from accessibility tools to virtual assistants and entertainment.