Sex differences in vocal behavior in virtual rooms compared to real rooms.

This study investigates speech production under various room acoustic conditions in virtual environments, by comparing vocal behavior and the subjective experience of speaking in four real rooms and their audio-visual virtual replicas. Sex differences were explored. Males and females (N = 13) adjusted their voice levels similarly to room acoustic changes in the real rooms, but only males did so in the virtual rooms. Females, however, rated the visual virtual environment as more realistic compared to males. This suggests a discrepancy between sexes regarding the experience of realism in a virtual environment and changes in objective behavioral measures such as voice level.

Gaussian processes for sound field reconstruction.

This study examines the use of Gaussian process (GP) regression for sound field reconstruction. GPs enable the reconstruction of a sound field from a limited set of observations based on the use of a covariance function (a kernel) that models the spatial correlation between points in the sound field. Significantly, the approach makes it possible to quantify the uncertainty on the reconstruction in a closed form. In this study, the relation between reconstruction based on GPs and classical reconstruction methods based on linear regression is examined from an acoustical perspective. Several kernels are analyzed for their potential in sound field reconstruction, and a hierarchical Bayesian parameterization is introduced, which enables the construction of a plane wave kernel of variable sparsity. The performance of the kernels is numerically studied and compared to classical reconstruction methods based on linear regression. The results demonstrate the benefits of using GPs in sound field analysis. The hierarchical parameterization shows the overall best performance, adequately reconstructing fundamentally different sound fields. The approach appears to be particularly powerful when prior knowledge of the sound field would not be available.

Large-scale outdoor sound field control.

The feasibility and the performance of controlling low frequency sound of loudspeaker systems under varying atmospheric conditions is examined experimentally. In the experiment, a control subwoofer array is canceling the sound of a primary subwoofer array over long distances (∼100 m) and in large areas (∼320 m2) using the pressure-matching method. To avoid the measurement of the sound field over the entire control area, a sound propagation model is introduced that is fitted in situ to model the radiation properties of the loudspeakers and the variation of the speed of sound. The results show that the control system reduces the sound pressure levels by up to 15-20 dB over the subwoofers' frequency range. However, the reduction can vary considerably depending on the specific atmospheric condition. The model-based approach reduces the number of required measurements and achieves similar reduction performance to the control based on direct measurements with considerably fewer microphone locations while also being more robust. Additionally, the sound propagation model enables the reduction of acoustic energy in virtual control zones that are far away from the microphone location. The investigated methodology has a direct application in the mitigation of sound from outdoor concerts.

A Bayesian spherical harmonics source radiation model for sound field control.

In sound field reproduction and sound field control systems, the acoustic transfer functions between a set of sources and an extended reproduction area need to be accurately estimated in order to achieve good performance. This implies that large amounts of measurements should be performed if the area is large compared to the wavelengths of interest. In this paper, a method for reconstructing these transfer functions in highly damped conditions is proposed by using only a small number of measurements in the reproduction area. The source radiation is modeled with the spherical harmonics basis and its amplitude coefficients are fitted with Bayesian inference. This approach is validated in a sound field control experiment where a set of 12 control loudspeakers attenuate the sound pressure level generated by a set of six primary loudspeakers in a quiet zone while minimizing their radiation into a listening zone. The performance of the approach is studied by analyzing the sound field reconstruction and the sound field control performance. It is shown that it is possible to get-with few measurements and the source radiation model-results similar to those achieved using a dense grid of transfer function measurements.

Active room compensation for sound reinforcement using sound field separation techniques.

This work investigates how the sound field created by a sound reinforcement system can be controlled at low frequencies. An indoor control method is proposed which actively absorbs the sound incident on a reflecting boundary using an array of secondary sources. The sound field is separated into incident and reflected components by a microphone array close to the secondary sources, enabling the minimization of reflected components by means of optimal signals for the secondary sources. The method is purely feed-forward and assumes constant room conditions. Three different sound field separation techniques for the modeling of the reflections are investigated based on plane wave decomposition, equivalent sources, and the Spatial Fourier transform. Simulations and an experimental validation are presented, showing that the control method performs similarly well at enhancing low frequency responses with the three sound separation techniques. Resonances in the entire room are reduced, although the microphone array and secondary sources are confined to a small region close to the reflecting wall. Unlike previous control methods based on the creation of a plane wave sound field, the investigated method works in arbitrary room geometries and primary source positions.