Singing Voice Conversion

Singing voice conversion (SVC) aims to transform one singer's voice into another while preserving musical content. Current research heavily utilizes diffusion models and generative adversarial networks (GANs), often incorporating techniques like feature disentanglement, self-supervised learning, and adversarial training to improve audio quality, robustness to noise, and inference speed. These advancements are significant for applications such as creating personalized song covers, enhancing accessibility for singers with vocal limitations, and addressing copyright concerns related to unauthorized voice manipulation.