Audio Quality

Audio quality research aims to objectively measure and improve the perceptual experience of sound, addressing challenges in accurately reflecting human listening preferences. Current efforts focus on developing robust reference-free metrics, leveraging machine learning models (including generative and self-supervised approaches) and deep neural networks to predict subjective quality scores and enhance audio for various applications, such as hearing aid optimization and speech enhancement. These advancements are crucial for improving the quality of audio across diverse applications, from music production and teleconferencing to assistive technologies and the development of more realistic virtual and augmented reality experiences.