The creation of sound zones with frequency-domain variable span trade-off filters (VAST) is investigated herein. Both narrowband and broadband discrete Fourier transform (DFT)-domain VAST approaches are proposed, and we discuss their relationship to the existing time-domain VAST approach. The core idea in VAST is to apply a generalized eigenvalue decomposition to the spatial statistics to control the trade-off between acoustic contrast and signal distortion. Moreover, a method for determining the optimal Lagrange multiplier that controls this trade-off is also considered in terms of physical, meaningful parameters. Through analysis and experiments, a performance comparison using measured room impulse responses is conducted not only between the two proposed methods but also between the two proposed methods and the existing time-domain approach. The results confirm that the broadband approach is able to transfer the acoustic contrast from one frequency bin to another, which is not the case for the narrowband approach. Furthermore, the results also show that the proposed DFT-domain VAST approach can be considered to be a special case of the time-domain VAST approach.

Personal sound zones provide users to experience independent listening and quiet areas in the same acoustic environment using multiple loudspeakers. The generalized eigenvalue decomposition (GEVD) has been proposed for sound zones generation, allowing user to control the trade-off between acoustic contrast and signal distortion by adjusting some parameters. Unfortunately, these parameters are not physically meaningful, and the user has to tune them for different source materials and acoustic environments. Moreover, performing a high dimensional GEVD is computational complex. In this article, we first propose various strategies to control the reproduced sound zones as precisely and accurately as possible by reformulating the problem using physically meaningful constraints using regularization approach. Then, a hybrid approach of combining the conjugate gradient method and GEVD is proposed to reduce the computational complexity and signal distortion when the subspace dimension is small. The proposed methods show precise control over the reproduced sound zone via extensive numerical simulations in reverberant environments for different physically meaningful constraints.

Sound zone control enables different users to enjoy different audio contents in the same acoustic environment. Generalized eigenvalue decomposition (GEVD)-based methods allow us to control the tradeoff between the acoustic contrast (AC) and signal distortion (SD). However, such methods have a high computational complexity. In this paper, we propose a fast reduced-rank sound zone control algorithm using the conjugate gradient (CG) method. Instead of using the eigenvectors as the basis for the solution space, the search directions in the CG method are used to reduce the computational complexity. Then, a low dimensional EVD is applied to obtain the sub-optimal control filter coefficients. The dark zone power can be adjusted by a parameter, which implicitly controls the trade-off between the AC and SD. Compared with GEVD-based methods, experimental results show that the proposed algorithm has a degradation of performance (4-5 dB) in terms of AC or SD but a high improvement on computational efficiency.

Creating sound zones has been an active research field since the idea was first proposed. So far, most sound zone control methods rely on either an optimization of physical metrics such as acoustic contrast and signal distortion or a mode decomposition of the desired sound field. By using these types of methods, approximately 15 dB of acoustic contrast between the reproduced sound field in the target zone and its leakage to other zone(s) has been reported in practical set-ups, but this is typically not high enough to satisfy the people inside the zones. In this article, we propose a sound zone control method shaping the leakage errors so that they are as inaudible as possible for a given acoustic contrast. The shaping of the leakage errors is performed by taking the time-varying input signal characteristics and the human auditory system into account when the loudspeaker control filters are calculated. We show how this shaping can be performed using variable span trade-off filters, and we show theoretically how these filters can be used for trading signal distortion in the target zone for acoustic contrast. The proposed method is evaluated based on physical metrics such as acoustic contrast and perceptual metrics such as STOI. The computational complexity and processing time of the proposed method for different system set-ups are also investigated. Lastly, the results of a MUSHRA listening test are reported. The test results show that the proposed method provides more than 20% perceptual improvement compared to existing sound zone control methods.

The creation of sound zones has been an active research topic for approximately two decades. Many sound zone control methods have been proposed, and the best approaches result in a target to interferer ratio (TIR) of about 15 dB in a practical set-up. Unfortunately, this is far from a TIR of about 25 dB which is currently believed necessary to make sound zones commercially viable. However, state-of-the-art sound zone control methods take neither the input signal characteristics nor human auditory perception into account. In this paper, we show how a recently proposed sound zone control framework called VAST can be extended into perceptual VAST (P-VAST) which takes input signal characteristics and human auditory perception into account. We also make a proof-of-concept simulation and an AB preference test which both show that P-VAST outperforms traditional sound zone control methods in terms of perceptually meaningful metrics such as STOI and PESQ in a fairly simple set-up.

Sound zones are typically created using Acoustic Contrast Control (ACC), Pressure Matching (PM), or variations of the two. ACC maximizes the acoustic potential energy contrast between a listening zone and a quiet zone. Although the contrast is maximized, the phase is not controlled. To control both the amplitude and the phase, PM instead minimizes the difference between the reproduced sound field and the desired sound field in all zones. On the surface, ACC and PM seem to control sound fields differently, but we here demonstrate they are actually extreme special cases of a much more general framework. The framework is inspired by the variable span linear filtering framework for speech enhancement. Using this framework, we demonstrate that 1) ACC gives the best contrast, but the highest signal distortion in the bright zone, and 2) PM gives the smallest signal distortion in the bright zone, but the worst contrast. Aside from showing this mathematically, we also demonstrate this via a small toy example.