Voice Cloning

Voice cloning uses machine learning to synthesize speech mimicking a specific person's voice, aiming to create realistic and personalized audio. Current research focuses on improving the naturalness and emotional expressiveness of cloned voices, often employing techniques like self-supervised learning and advanced neural network architectures such as VITS2 and diffusion models, while also addressing challenges in cross-lingual cloning and low-resource scenarios. This field is significant due to its applications in personalized interfaces, dubbing, and accessibility technologies, but also raises ethical concerns regarding misuse for malicious purposes like deepfakes and impersonation, leading to active research in detection and watermarking techniques.