The field of acoustic research is moving towards more accurate and efficient methods for modeling and sensing acoustic phenomena. Recent developments have focused on improving the estimation of acoustic surface impedances, soil moisture monitoring, and neural acoustic modeling. These advancements have the potential to impact various applications, including sound simulation, agriculture, and environmental management. Noteworthy papers include:

• A study on in situ estimation of acoustic surface impedances using simulation-based inference, which achieved robust and accurate estimation of impedance behavior.
• SoilSound, a smartphone-based system for soil moisture estimation, which demonstrated high accuracy and reliability without requiring calibration or disturbing the soil.
• The introduction of WINNER, a method for improving the accuracy and efficiency of implicit neural representations, which achieved state-of-the-art results in audio and image fitting tasks.
• The development of MiNAF, a neural acoustic modeling approach that incorporates explicit geometric information, which demonstrated competitive performance in generating accurate room impulse responses.