Speech Distortion

Speech distortion, encompassing degradation of speech signals due to noise, transmission errors, or physiological impairments, is a significant challenge across various applications, from hearing aids to voice assistants. Current research focuses on developing robust speech enhancement and restoration models, often employing deep learning architectures like diffusion models, transformers, and U-Nets, to improve speech quality and intelligibility by leveraging both acoustic and visual cues, or by incorporating self-supervised learning and knowledge distillation techniques. These advancements aim to improve the performance of downstream tasks such as automatic speech recognition and speech quality assessment, ultimately impacting the accessibility and usability of speech-based technologies for individuals with hearing impairments and in noisy environments.