Geometrical room geometry estimation from room impulse responses

Abstract

Room geometry estimation from corresponding Room Impulse Responses (RIRs) has attracted much attention in recent years, and a key challenge is to find the first order image source locations from the RIRs under different environments. Unlike the existing approaches which require a priori knowledge of the room or require some ideal conditions, this paper proposes an intuitive geometrical method based on the acoustical image source model. The proposed approach does not need any a priori knowledge of the room, only the RIRs from one arbitrary source location to five arbitrary receiving locations. The first order image sources of the walls in a room are identified first, then the room geometry is estimated based on the wall locations using a geometrical approach. Simulations with 2D and 3D convex polyhedral rooms demonstrate the feasibility and the precision of the proposed approach is discussed.

Can a phone hear the shape of a room?

“…In the 1960's, Kac famously lectured about a solution for solving the age-old physics problem of estimating the geometry of a drum based on the sound generated from striking the surface. More recently, this problem has been extended to estimating the shape of rooms based on their acoustic RIR [3,8,11,17,24,30,31,36]. Acoustic geometry reconstruction typically assumes a set of microphones and speaker arrays with known locations.…”

“…These transmit and receive pairs estimate the location of walls and obstacles based on the time delays of echoes. Most approaches rely on measuring the RIR and ind the most likely location of walls based on the signals' time of arrival (TOA) [8,11,17,30,31,36] or time diference of arrival (TDOA) [3,24] of impulses, depending on whether the speakers and microphones are synchronized. One approach models walls as planar surfaces tangent to the ellipsoid deined by the distance between transmitter/receiver pairs [3,31].…”

“…In the early 1900's, Sabine began to model the impact of people, frequency and the geometry of spaces on acoustics [32]. Signiicant follow-on work has explored modeling sound in indoor spaces to the point where it is possible to use the arrival time of echoes relected of of walls to reconstruct room geometry [3,8,11,17,24,30,31,36]. These approaches leverage the RIR to ind the most likely position of walls in space using a set of speakers and microphones in a ixed and well-known coniguration.…”

Can a Robot Hear the Shape and Dimensions of a Room?

“…1, the first ISs arrive arbitrarily, corresponding to the second, third, fifth and eleventh peaks, respectively. Therefore, in practice, it has been proposed to employ multiple acoustic sensors for room shape estimation [5], and in this work four microphones are employed to reconstruct the shape of a 2D polygonal room [11].…”

“…Here τ 1 , τ 2 and τ 3 are one of the TOAs on the RIRs collected by mc.i 1, 2 and 3, respectively. As discussed in our previous work [11], an additional fourth acoustic sensor is employed to verify the common ISs. In other words, two other equations similar to (3) can be established and solved, then three sets of solutions are exploited to sort out the common ISs.…”