AudioAI
AI that pulls the vocals out—fast Ever wished you could solo a singer from any track without artifacts? This research shows how, using a latent diffusion model that separates vocals from full mixes. * Efficient: Generates in a compact audio latent space, then decodes to sound—speeding up training and
AudioAI
Ever wanted studio‑clean vocals from any song? This research introduces a generative system that separates singing voices from full mixes using a latent diffusion model. How it works * Generates audio in a compact latent space, then decodes it back to sound—making training and inference efficient. * Trained only on
AudioAI
Ever wished your mic could zoom in on the right voice, even in a noisy room? This research shows how. An on-device deep learning tracker works with a compact ring-shaped array of tiny MEMS microphones to steer a "listening beam" in real time—locking onto a moving target
AudioAI
Remixes, sped-up clips, and heavy compression make it hard to trace where music on social platforms comes from. This study introduces more robust neural audio fingerprints—compact “IDs” for audio—that can still recognize a song after it’s been distorted. * Music-first brains: Instead of training from scratch, the model