AudioSphere learns spatial audio from multichannel self-supervision: a frozen backbone localizes real-world sound events for the first time
AudioSphere extends self-supervised audio pretraining from single-channel to multichannel: it takes four-channel Ambisonics recordings and trains a masked autoencoder to reconstruct both spectrograms and intensity vectors, so a frozen backbone with a shallow probe performs sound event detection and localization in real scenes. Prior single-channel models were blind to spatial structure, while spatial models relied on clip-level supervision. It reaches an aggregate HEAR score of 83.2 and also supports frame-level localization.