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Psychoacoustic experiments have shown that directional properties of the direct sound, salient reflections, and the late reverberation of an acoustic room response can have a distinct influence on the auditory perception of a given room. Spatial room impulse responses (SRIRs) capture those properties and thus are used for direction-dependent room acoustic analysis and virtual acoustic rendering. This work proposes a subspace method that decomposes SRIRs into a direct part, which comprises the direct sound and the salient reflections, and a residual, to facilitate enhanced analysis and rendering methods by providing individual access to these components. The proposed method is based on the generalized singular value decomposition and interprets the residual as noise that is to be separated from the other components of the reverberation. Large generalized singular values are attributed to the direct part, which is then obtained as a low-rank approximation of the SRIR. By advancing from the end of the SRIR toward the beginning while iteratively updating the residual estimate, the method adapts to spatio-temporal variations of the residual. The method is evaluated using a spatio-spectral error measure and simulated SRIRs of different rooms, microphone arrays, and ratios of direct sound to residual energy. The proposed method creates lower errors than existing approaches in all tested scenarios, including a scenario with two simultaneous reflections. A case study with measured SRIRs shows the applicability of the method under real-world acoustic conditions. A reference implementation is provided.

Spherical harmonic (SH) representations of sound fields are usually obtained from microphone arrays with rigid spherical baffles whereby the microphones are distributed over the entire surface of the baffle. We present a method that overcomes the requirement for the baffle to be spherical. Furthermore, the microphones can be placed along a circumferential contour around the baffle. This greatly reduces the required number of microphones for a given spatial resolution compared to conventional spherical arrays. Our method is based on the analytical solution for SH decomposition based on observations along the equator of a rigid sphere that we presented recently. It incorporates a calibration stage in which the microphone signals due to a suitable set of calibration sound fields are projected onto the SH decomposition of those same sound fields on the surface of a notional rigid sphere by means of a linear filtering operation. The filter coefficients are computed from the calibration data via a least/squares fit. We present an evaluation of the method based on the application of binaural rendering of the SH decomposition of the signals from an 18/element array that uses a human head as the baffle and that provides 8th ambisonic order. We analyse the accuracy and robustness of our method based on simulated data as well as based on measured data from a prototype.

Additive noise produced by the recording hardware will contribute to streamed signals from spherical microphone arrays under practical conditions. For the application of binaural reproduction and under the assumption that the noise is uncorrelated between the array channels, the spectral properties and the overall level of the rendered noise in the ear signals have been shown to be strongly influenced by the configuration of the array as well as of the processing pipeline. In a previous investigation, we determined the audibility thresholds for changes in the rendered noise due to listener head rotations as a function of the differences in noise level of individual array channels. In this article, we calibrate the instrumental metric of Composite Loudness Level to the perceptual data and predict audibility of changes in the additive noise due to head rotations for a broad set of array configurations and distributions of the noise levels across array channels. We demonstrate that some types of microphone layouts can produce audible variations even if the noise level is equal in all channels. This is particularly the case for sampling grids that exhibit negative quadrature weights such as the Lebedev and Fliege-Maier grids for some spherical harmonic orders. The analysis of configurations with unevenly distributed noise contributions show that the influence of the noise from individual array channels is determined by the proximity of their virtual location to the relative trajectory of the ears.

The measurement of directivity for sound sources that are not electroacoustic transducers is fundamentally limited because the source cannot be driven with arbitrary signals. A consequence is that directivity can only be measured at a sparse set of frequencies—for example, at the stable partial oscillations of a steady tone played by a musical instrument or from the human voice. This limitation prevents the data from being used in certain applications such as time-domain room acoustic simulations where the directivity needs to be available at all frequencies in the frequency range of interest. We demonstrate in this article that imposing the signature of the directivity that is obtained at a given distance on a spherical wave allows for all interpolation that is required for obtaining a complete spherical harmonic representation of the source's directivity, i.e., a representation that is viable at any frequency, in any direction, and at any distance. Our approach is inspired by the far-field signature of exterior sound fields. It is not capable of incorporating the phase of the directivity directly. We argue based on directivity measurement data of musical instruments that the phase of such measurement data is too unreliable or too ambiguous to be useful. We incorporate numerically-derived directivity into the example application of finite difference time domain simulation of the acoustic field, which has not been possible previously.

Local sound field synthesis allows for synthesizing a given desired sound field inside a limited target region such that the field is free of considerable spatial aliasing artifacts. Spatial aliasing artifacts are a consequence of overlaps due to unavoidable repetitions of the space-spectral coefficients of the secondary source driving function. We analyze various conceivable analytic ways of restricting the bandwidth of the spatial spectrum of the driving function such that considerable overlapping is prevented: local spatial bandlimitation (A), spectral windowing (B), and local spatial band-limitation plus spectral windowing (C). While solution B is computationally significantly more efficient than A and C, it provides only limited control over the spatial location around which the aliasing-free region evolves. Solutions A and C provide more flexibility and higher accuracy whereby both achieve largely identical results so that the spectral windowing after the local spatial bandlimitation may be skipped. We present a detailed analysis of the properties of the spatial aliasing artifacts arising in the synthesis of a virtual plane wave. We establish a procedure for predicting the maximum possible size of the aliasing-free target region depending on its location and on the propagation direction of the desired sound field. The results can help reducing regularization in numerical solutions as they represent physical limitations that can be considered in the choice of parameters.