Neural Audio Synthesis

Neural audio synthesis aims to generate high-fidelity audio using deep learning models, focusing on achieving both realism and controllable manipulation of sound characteristics. Current research emphasizes developing models that offer intuitive control over synthesized audio, exploring architectures like variational autoencoders (VAEs), generative adversarial networks (GANs), and differentiable digital signal processing (DDSP) to achieve this. These advancements are significant for both scientific understanding of audio generation and practical applications, including music production, sound design, and speech processing, by providing powerful tools for creating and manipulating sounds.