Room geometry inference is concerned with the localization of reflective boundaries in an enclosed space. This paper outlines a method for inferring room geometry based on the positions of loudspeakers and real or image microphones, which are computed using sets of times of arrival (TOAs) obtained from room impulse responses (RIRs). These RIRs describe the acoustic propagation between the loudspeakers in an array and a single microphone. First, peaks corresponding to TOAs in these RIRs are detected and labeled using an automated method. Second, the labeled TOA sets are used to estimate the real and image microphone positions, with knowledge of the loudspeaker array geometry. Third, using all these positions, the positions of reflection points on the available reflectors in the room are determined. The reflection points determine the reflectors' locations and orientations. This approach is largely automated and usable in real-world scenarios.

Echo labeling, the challenging task of assigning acoustic reflections to image sources, is equivalent to the highly-important disambiguation task in room geometry inference. A method using the Radon transform, an image processing tool, is proposed to address this challenge. The method relies on acoustic wavefront detection in room impulse response stacks, obtained with a uniform linear array of loudspeakers and one microphone. We show in our experiments that the proposed method can both label and detect echoes.