High Fidelity Audio

High-fidelity audio research aims to generate and manipulate audio with exceptional realism and detail, focusing on improving the quality of synthesized speech, music, and environmental sounds. Current efforts leverage advanced deep learning models, including diffusion models, generative adversarial networks (GANs), and transformer networks, often incorporating multi-band processing and latent space manipulation for efficient and high-quality audio generation and restoration. This field is crucial for advancements in various applications, such as immersive media, music production, audio restoration, and speech technology, driving improvements in both the subjective listening experience and objective audio quality metrics.