Deep Subband

Deep subband processing enhances signal processing by decomposing signals into multiple frequency subbands for independent processing before recombining. Current research focuses on integrating deep learning architectures, such as deep neural networks and filter-bank equalizers, to improve performance in applications like speech enhancement and dereverberation, often targeting low-latency solutions. These advancements aim to improve the robustness and efficiency of algorithms dealing with noisy or reverberant signals, impacting fields such as hearing aid technology and audio communication. Robustness to various noise types, including impulse noise, is a key area of ongoing development.