Sound Separation

Sound separation aims to isolate individual sound sources from a mixture, a crucial task with applications ranging from hearing aids to music production. Current research emphasizes developing robust models, including generative approaches like diffusion models and variational autoencoders, as well as refined beamforming techniques and those leveraging both audio and visual information. These advancements are driven by the need for improved separation accuracy, particularly in challenging scenarios with overlapping sounds or noisy environments, ultimately impacting fields like audio engineering, assistive technologies, and anomaly detection.