Voice Style Transfer

Voice style transfer (VST) aims to convert speech to sound like a different speaker while preserving the original linguistic content. Current research heavily utilizes diffusion models and convolutional neural networks, often incorporating hierarchical architectures and disentangled representations to improve control over specific voice characteristics like pitch and timbre, and address challenges like zero-shot conversion and robust speaker adaptation. This field is significant for its potential applications in speech synthesis, accessibility technologies, and entertainment, while also raising ethical concerns regarding speaker impersonation and traceability that are actively being addressed through techniques like speaker embedding and watermarking.