Adaptive, generalized and personalized preference models for speech enhancement
Background Speech enhancement, the process of improving the quality speech signals, can not only improve quality of experience for listeners and the quality of communication, it can also aid the performance of machine-and deep-learning models in downstream tasks. However, the challenge of the trade-off between noise removal and artifact incorporation is ongoing [1]. The project aims to investigate the factors influencing noise reduction preferences and develop a technical framework around it. Low data-resources will be an important consideration in this project. ...