Room Acoustic
Room acoustics research focuses on understanding and manipulating the sound field within enclosed spaces, aiming to improve sound quality, localization, and speech intelligibility. Current research emphasizes developing advanced models, such as diffusion models and feedback delay networks, for accurate room impulse response (RIR) estimation and synthesis, often incorporating machine learning techniques for blind dereverberation and parameter estimation from single-channel recordings. These advancements have significant implications for various applications, including virtual and augmented reality, audio processing algorithms, and the design of more effective acoustic environments.
Papers
Evaluation of Virtual Acoustic Environments with Different Acoustic Level of Detail
Stefan Fichna, Steven van de Par, Stephan D. Ewert
On the relevance of acoustic measurements for creating realistic virtual acoustic environments
Siegfried Gündert, Stephan D. Ewert, Steven van de Par
Computationally-efficient and perceptually-motivated rendering of diffuse reflections in room acoustics simulation
Stephan D. Ewert, Nico Gößling, Oliver Buttler, Steven van de Par, Hongmei Hu