Towards fully uncalibrated room reconstruction with sound

This paper presents a novel approach for room reconstruction using unknown sound signals generated in different locations of the environment. The approach is very general, that is fully uncalibrated, i.e. the locations of microphones, sound events and room reflectors are not known a priori. We show that, even if this problem implies a highly non-linear cost function, it is still possible to provide a solution close to the global minimum. Synthetic experiments show the proposed optimization framework can achieve reasonable results even in the presence of signal noise.