Experimental Analysis of Individual Listening Zone Algorithms in Controlled Environments

Acoustic contrast control (ACC) and pressure matching (PM) are advanced digital signal processing algorithms aimed at designing finite impulse response (FIR) filters to control the sound field and establish individual listening zones. These techniques require the tuning of some parameters, such as regularization factor and control points used for optimization, and proper use of some metrics, such as array effort and desired sound level, which affect their performance. In this paper, a comparison in terms of acoustic contrast (AC) and fidelity of the reproduced sound field achieved by PM and ACC is presented. The performance analysis is based on numerical simulations considering the channels described by impulse responses (IRs) of loudspeaker-microphone pairs measured in controlled indoor environments. A near-ideal acoustic channel is obtained by truncating the IRs, measured in a large room, after the direct component of the sound. The results obtained for the near-ideal channel show performance in agreement with the optimization criterion of each considered algorithm. This behavior is less evident using realistic IRs, where the performance tends to become equivalent for all the discussed methods. These results lead to the fact that, in applications to realistic scenarios, the chosen optimization criterion may have less impact on the performance, which may be affected by other system parameters, such as the geometrical configurations of the used loudspeakers and the acoustic zones of interest.