Acoustic Measurement

Acoustic measurement focuses on precisely characterizing sound propagation and its interaction with environments, aiming to quantify parameters like sound speed, attenuation, and reverberation time. Current research emphasizes developing robust and efficient measurement techniques, including the application of deep learning models (e.g., U-Net architectures) for improved accuracy and automation, particularly in challenging scenarios like noisy environments or using non-traditional sound sources. These advancements are crucial for various applications, ranging from improving the realism of virtual acoustic environments to enabling minimally invasive medical procedures and optimizing room acoustics in architectural design.