Towards an End-to-End Visual-to-Raw-Audio Generation With GAN

Automatically synthesizing sounds for different visual contents poses a challenge and there is a strong need to facilitate the direct creation of realistic sounds. Different from previous works, in this paper, we propose a novel deep learning based approach, which formulates sound simulation as a regression problem. This allows us to circumvent the complexity of the acoustic theory by a novel, gen...