Room Geometry Inference Using Localization of the SoundSource and Its Early Reflections - Donghang Wu; Xihong Wu; Tianshu Qu (the AES 158th Convention, 2025)
Traditional methods for inferring room geometry from sound signals are predominantly based on Room ImpulseResponse (RIR) or prior knowledge of the sound source location. This significantly restricts the applicability ofthese approaches. This paper presents a method for estimating room geometry based on the localization of directsound source and its early reflections from First-Order Ambisonics (FOA) signals without the prior knowledge ofthe environment. First, this method simultaneously estimates the Direction of Arrival (DOA) of the direct sourceand the detected first-order reflected sources. Then, a Cross-attention-based network for implicitly extractingthe features related to Time Difference of Arrival (TDOA) between the direct source source and the first-orderreflected sources is proposed to estimate the distances of the direct and the first-order reflected sources. Finally,the room geometry is inferred from the localization results of the direct and the first-order reflected sources. Theeffectiveness of the proposed method was validated through simulation experiments. The experimental resultsdemonstrate that the method proposed achieves accurate localization results and performs well in inference of roomgeometry.