Audio Super Resolution

Audio super-resolution (ASR) aims to enhance the quality of low-resolution audio recordings by reconstructing missing high-frequency components. Current research focuses on developing robust and versatile models, employing diverse architectures such as diffusion models, generative adversarial networks (GANs), and encoder-decoder networks, often incorporating techniques like spectral domain processing and phase repair to improve perceptual quality across various audio types and bandwidths. These advancements are significant for improving the fidelity of existing audio recordings and enabling real-time applications, such as enhancing bone conduction microphone output and improving the performance of other audio generative models.