Speech Restoration

Speech restoration aims to recover high-quality audio from degraded recordings, addressing issues like noise, reverberation, bandwidth limitations, and clipping. Current research heavily utilizes generative models, including diffusion models and GANs, often incorporating techniques like masked language modeling and complex-valued signal processing to achieve superior performance compared to traditional discriminative methods. This field is crucial for improving speech intelligibility in various applications, from enhancing historical recordings to improving the quality of speech-based assistive technologies and creating more robust speech datasets for training machine learning models.