Adaptive optimization of the trade-off parameter in acoustic-contrast-control-pressure-matching for personal audio zones using genetic algorithms

This paper is dedicated to solving the intrinsic problems of the traditional acoustic-contrast-control-pressure-matching (ACC-PM) algorithm that is commonly applied to realize the so-called personal audio zone (PAZ) concept. This is achieved by optimizing the trade-off parameter in the ACC-PM algorithm using the genetic algorithm (GA). Upon optimization, the trade-off parameter is no longer constant but becomes frequency- and circumstance-dependent. In-situ measurements demonstrate that the optimization can, in general, improve the sound compartmentalization performance of the PAZ system and, more importantly, enhance the numerical stability of the ACC-PM algorithm, making it more robust for practical application. An effective way to implement the optimization in practice is recommended at the end of the paper.