Sound Field

Sound field research focuses on understanding and manipulating the spatial distribution of acoustic pressure, aiming to accurately capture, reproduce, and control sound in three-dimensional space. Current research emphasizes developing advanced models and algorithms, including physics-informed neural networks, conditional invertible neural networks, and various forms of harmonic decomposition and kernel interpolation, to improve the accuracy and efficiency of sound field estimation and synthesis from limited measurements. These advancements have significant implications for applications such as spatial audio, active noise control, and virtual/augmented reality, offering more realistic and immersive auditory experiences.