Personalized Speech

Personalized speech synthesis aims to generate synthetic speech that accurately reflects an individual's unique vocal characteristics, including timbre, prosody, and emotional expression. Current research focuses on developing efficient methods for adapting large language models and neural vocoders to limited speaker data, often employing techniques like parameter-efficient fine-tuning, multi-center speaker embeddings, and adversarial training to enhance voice quality and individuality while mitigating privacy concerns. This field holds significant potential for applications ranging from assistive technologies for individuals with speech impairments to creating more engaging and realistic virtual characters in entertainment and e-commerce.