Room impulse response reconstruction with physics-informed deep learning.

A method is presented for estimating and reconstructing the sound field within a room using physics-informed neural networks. By incorporating a limited set of experimental room impulse responses as training data, this approach combines neural network processing capabilities with the underlying physics of sound propagation, as articulated by the wave equation. The network's ability to estimate particle velocity and intensity, in addition to sound pressure, demonstrates its capacity to represent the flow of acoustic energy and completely characterise the sound field with only a few measurements.

Generative adversarial networks with physical sound field priors.

This paper presents a deep learning-based approach for the spatiotemporal reconstruction of sound fields using generative adversarial networks. The method utilises a plane wave basis and learns the underlying statistical distributions of pressure in rooms to accurately reconstruct sound fields from a limited number of measurements. The performance of the method is evaluated using two established datasets and compared to state-of-the-art methods.

Generative models for sound field reconstruction.

This work examines the use of generative adversarial networks for reconstructing sound fields from experimental data. It is investigated whether generative models, which learn the underlying statistics of a given signal or process, can improve the spatio-temporal reconstruction of a sound field by extending its bandwidth. The problem is significant as acoustic array processing is naturally band limited by the spatial sampling of the sound field (due to the difficulty to satisfy the Nyquist criterion in space domain at high frequencies).

Acousto-optic holography.

Acousto-optic sensing is based on the interaction between sound and light: pressure waves induce density variations, which, in turn, alter the way light propagates in air. Pressure fields are, thus, characterized by measuring changes in light propagation induced by pressure waves. Although acousto-optic sensing provides a way of acquiring acoustic information noninvasively, its widespread application has been hindered by the use of reconstruction methods ill-suited for representing acoustic fields.

A convolutional plane wave model for sound field reconstruction.

Spatial sound field interpolation relies on suitable models to conform to available measurements and predict the sound field in the domain of interest. A suitable model can be difficult to determine when the spatial domain of interest is large compared to the wavelength or when spherical and planar wavefronts are present or the sound field is complex, as in the near-field. To span such complex sound fields, the global reconstruction task can be partitioned into local subdomain problems.

Sound source localization using multiple ad hoc distributed microphone arrays.

Sound source localization is crucial for communication and sound scene analysis. This study uses direction-of-arrival estimates of multiple ad hoc distributed microphone arrays to localize sound sources in a room. An affine mapping between the independent array estimates and the source coordinates is derived from a set of calibration points.

Four decades of near-field acoustic holography.

The Reflections series takes a look back on historical articles from The Journal of the Acoustical Society of America that have had a significant impact on the science and practice of acoustics.

Analysis of the sound field above finite absorbers in the wave-number domain.

This study examines the edge diffraction effect when a sound wave impinges and reflects off finite porous absorbers, flush-mounted in an infinite hard baffle. A theoretical analysis of the diffraction is given by taking a two-dimensional spatial Fourier transform of a plane wave impinging on a finite absorber. Numerical experiments are also presented to simulate the sound field above infinite and finite locally reactive absorbers and the measurement with an array of pressure sensors.

Spatial reconstruction of the sound field in a room in the modal frequency range using Bayesian inference.

Spatial characterization of the sound field in a room is a challenging task, as it usually requires a large number of measurement points. This paper presents a probabilistic approach for sound field reconstruction in the modal frequency range for small and medium-sized rooms based on Bayesian inference. A plane wave expansion model is used to decompose the sound field in the examined domain.

Spatial reconstruction of sound fields using local and data-driven functions.

Sound field analysis methods make it possible to characterize and reconstruct a sound field from a limited set of observations. Classical approaches rely on the use of analytical basis functions to model the sound field throughout the observed domain. When the complexity of the sound field is high, for example, in a room at mid and high frequencies, propagating wave representations can be suboptimal due to model discrepancy.

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.

Sparse planar arrays for azimuth and elevation using experimental data.

Sparse arrays are special geometrical arrangements of sensors which overcome some of the drawbacks associated with dense uniform arrays and require fewer sensors. For direction finding applications, sparse arrays with the same number of sensors can resolve more sources while providing higher resolution than a dense uniform array. This has been verified numerically and with real data for one-dimensional microphone arrays.

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 m) 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.

Isotropy in decaying reverberant sound fields.

A method of evaluating sound field isotropy in decaying reverberant sound fields is presented. The proposed method extends the experimental framework outlined in [J. Acoust.

Three-dimensional source localization using sparse Bayesian learning on a spherical microphone array.

The identification of acoustic sources in a three-dimensional (3D) domain based on measurements with an array of microphones is a challenging problem: it entails the estimation of the angular position of the sources (direction of arrival), distance relative to the array (range), and the quantification of the source amplitudes. A 3D source localization model using a rigid spherical microphone array with spherical wave propagation is proposed. In this study, sparse Bayesian learning is used to perform localization in 3D space and examine the use of principal component analysis to denoise the measurement data.

Reproducing ear-canal reflectance using two measurement techniques in adult ears.

Clinical diagnostic applications of ear-canal reflectance have been researched extensively in the literature, however, the measurement uncertainty associated with the conventional measurement technique using an insert ear probe is unknown in human ear canals. Ear-canal reflectance measured using an ear probe is affected by multiple sources of error, including incorrect estimates of the ear-canal cross-sectional area and oblique ear-probe insertions. In this paper, ear-canal reflectance measurements are reproduced in an occluded-ear simulator and in 54 adult ear canals using two different measurement techniques: a conventional ear probe and a two-microphone probe that enables the separation of reverse- and forward-propagating plane waves.

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.

Characterization of sound scattering using near-field pressure and particle velocity measurements.

The acoustic properties of surfaces are commonly evaluated using samples of finite size, which generate edge diffraction effects that are often disregarded. This study makes use of sound scattering theory to characterize such finite samples. In a given sound field, the samples can be described by a unique complex directivity function called the far-field pattern.

Comparison of two microphone array geometries for surface impedance estimation.

This study examines the estimation of the surface impedance of an absorber with microphone arrays. Two array geometries are compared-a rigid spherical array and a double layer planar array. The impedance is estimated via reconstructing the sound field (pressure and particle velocity) on the absorber's surface, using a plane wave expansion.

Compensating for oblique ear-probe insertions in ear-canal reflectance measurements.

Measurements of the ear-canal reflectance using an ear probe require estimating the characteristic impedance of the ear canal in situ. However, an oblique insertion of the ear probe into a uniform waveguide prevents accurately estimating its characteristic impedance using existing time-domain methods. This is caused by the non-uniformity immediately in front of the ear probe when inserted at an oblique angle, resembling a short horn loading, and introduces errors into the ear-canal reflectance.

Volumetric reconstruction of acoustic energy flows in a reverberation room.

This study examines the spatial and directional properties of net energy flows in a reverberation chamber. Based on measurements with a spherical array, a method is proposed to estimate the flows of acoustic energy in the volume surrounding the array. The proposed method is used to examine the steady state, early decay, and late decay of the sound field in a reverberation room (both empty and with an absorber on the floor).

Experimental characterization of the sound field in a reverberation room.

Measured values of acoustic absorption obtained from standardized reverberation-chamber measurements often differ across laboratories. These discrepancies arise due to non-isotropic sound incidence on the absorbing specimen, diffraction at the sample edges, and differences in the chambers' shapes and dimensions. The present study examines an experimental method for characterizing the distribution of sound incidence on the specimen in the steady state.

A coupler-based calibration method for ear-probe microphones.

The calibration of ear-probe microphones can increase the precision of calibrating stimulus levels and of measuring acoustic responses from the ear. This paper proposes a methodology to measure the sensitivity of an ear-probe microphone, requiring only an acoustic coupler and a calibrated reference microphone. The input impedance of the coupler is measured, enabled by a preliminary acoustic Thévenin calibration of the ear probe, and the plane-wave transfer impedance of the coupler is calculated analytically.

Reconstruction of the sound field in a room using compressive sensing.

Capturing the impulse or frequency response functions within extended regions of a room requires an unfeasible number of measurements. In this study, a method to reconstruct the response at arbitrary points based on compressive sensing (CS) is examined. The sound field is expanded into plane waves and their amplitudes are estimated via CS, obtaining a spatially sparse representation of the sound field.

Compressive acoustic holography with block-sparse regularization.

Sparse reconstruction methods, such as Compressive Sensing, are powerful methods in acoustic array processing, as they make wideband reconstruction possible. However, when addressing sound fields that are not necessarily sparse (e.g.