Volume 125, Issue 4, April 2009
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
125(2009); http://dx.doi.org/10.1121/1.3082114View Description Hide Description
A personal audio system that does not use earphone or any wire would have great interest and potential impact on the audio industries. In this study, a line array speaker system is used to localize sound in the listening zone. The contrast control [Choi, J.-W. and Kim, Y.-H. (2002). J. Acoust. Soc. Am.111, 1695–1700] is applied, which is a method to make acoustically bright zone around the user and acoustically dark zone in other regions by maximizing the ratio of acoustic potential energy density between the bright and the dark zone. This ratio is regarded as acoustic contrast, analogous with what is used for optical devices. For the evaluation of the performance of acoustic contrast control, experiments are performed and the results are compared with those of uncontrolled case and time reversal array.
125(2009); http://dx.doi.org/10.1121/1.3089221View Description Hide Description
Beamforming is done with an array of sensors to achieve a directional or spatially-specific response by using a model of the arriving wavefront. Real acoustic sources may deviate from the conventional plane wave or monopole model, causing decreased array gain or a total breakdown of beamforming. An alternative to beamforming with the conventional source model is presented which avoids this by using a more general source model. The proposed method defines a set of “sub-beamformers,” each designed to respond to a different spatial mode of the source. The outputs of the individual sub-beamformers are combined in a weighted sum to give an overall output of better quality than that of a conventional (monopole) beamformer. It is shown that with appropriate weighting, the optimum array gain can be achieved. A simple method is demonstrated to estimate the weighted sum, based on the observed data. The variance and bias of the estimate in the presence of noise are evaluated. Simulation and experimentally measured results are shown for a simple directive source. In the experiment, the proposed method provides an array gain of about 11 dB while beamforming using a point source model achieves only −4 dB.
125(2009); http://dx.doi.org/10.1121/1.3079773View Description Hide Description
To avoid the requirement set by standard near-field acoustical holography (NAH) to measure an area that fully covers the source, a set of so-called patch NAH methods has been introduced. One such method is the statistically optimized NAH (SONAH). In this method, the acoustic quantities on a mapping surface near the measurement surface are calculated by using a transfer matrix defined in such a way that all propagating waves and a weighted set of evanescent waves are projected with optimal average accuracy. The present paper gives an overview of the basic theory of SONAH, including a description of phenomena such as spatial aliasing and wave-number domain leakage. A revised and generalized mathematical formulation is given, covering the calculation of all three components of particle velocity and the use of up to six virtual source planes. A set of formulas for the inherent estimation error level of the method is derived and used to visualize the regions of validity of the SONAH predictions for some typical microphone array geometries. The sensitivity of the inherent error level distribution to changes in the parameters of the SONAH algorithm is also investigated.
Multiple-point statistical room correction for audio reproduction: Minimum mean squared error correction filtering125(2009); http://dx.doi.org/10.1121/1.3075615View Description Hide Description
This paper treats the problem of correction of loudspeaker and room responses using a single source. The objective is to obtain a linear correction filter, which is robust with respect to listener movement within a predefined region-of-interest. The correction filter is based on estimated impulse responses, obtained at several positions, and a linear minimum mean squared error criteria. The impulse responses are estimated using a Bayesian approach that takes both model errors and measurementnoise into account, which results in reliable impulse response estimates and a measure of the estimation errors. The correction filter is then constructed by using information from both the estimated impulse response coefficients and their associated estimation errors. Furthermore, in the optimization criteria a time-dependent reflection filter is introduced, which attenuates the high frequency parts of the reflected responses, that is, the parts of the responses that cannot be compensated with a single source system. The resulting correction filter is shown to significantly improve both the temporal and spectral properties of the responses compared to the uncorrected system, and, furthermore, the obtained correction filter has a low level of pre-ringing.