Sound Field Decomposition

Sound field decomposition aims to separate and reconstruct individual sound sources from a mixture of sounds recorded by multiple microphones, enabling accurate spatial audio reproduction and source localization. Current research focuses on developing neural network-based methods, including those employing implicit representations like Neural Acoustic Fields (NAFs) and warping fields, to model sound propagation and predict acoustic effects at arbitrary locations, often incorporating visual data to improve accuracy. These advancements are significantly improving the realism and accuracy of spatial audio applications and providing valuable tools for researchers in acoustics, robotics, and virtual/augmented reality.