The study of spatial audio and room acoustics aims to create immersive audio experiences by modeling the physics and psychoacoustics of how sound behaves in space. In the long history of this research area, various key technologies have been developed based both on theoretical advancements and practical innovations. We highlight historical achievements, initiative activities, recent advancements, and future outlooks in the research area of spatial audio recording and reproduction, and room acoustic simulation, modeling, analysis, and control.

Spatial active noise control (ANC) systems aim to control the noise field over a spatial region. However, when both the desired field and the interference field co-exist, typical ANC systems lack the ability to selectively reduce the interference field, resulting in distortions in the desired field. In this paper, we design a spherical-harmonic domain selective spatial ANC system to reduce the interference field and preserve the desired field. The designed system integrates a desired field extraction (DFE) process, a sound field reproduction (SER) process, and an ANC process. The DFE and SFR processes are implemented to first capture and then reproduce the desired field, while the ANC process reduces the pseudo residual field. The simulation study shows that compared to two existing ANC solutions, the proposed design achieves a better overall performance with an acceptable speech-distortion-ratio within the sweet area in a reverberant environment

Spatial Active noise control (ANC) systems are proposed to minimize the noise over a spatial region of interest around people’s heads by generating an anti-noise field with multiple microphones and loudspeakers. Recently, a realistic microphone geometry was designed to allow the system to monitor the residual noise field without restricting people’s head movement. However, this design, which utilizes the remote microphone technique using an observation filter (OF) for noise field modelling, has a drawback that the system is not robust against variations in the noise source location. In this paper, we address this drawback and present an improved spatial ANC system that overcomes this limitation. The proposed system enhances its adaptability by selectively employing the most suitable OF from a set of pre-modelled discriminator filter (DF), tailored to the acoustic environment of the system. We demonstrate that the proposed method maintains noise reduction performance over the region of interest with a dynamic noise source with changing position and signal through simulation and physical measurements.

Spatial audio reproduction and translation for virtual, augmented, and extended reality applications require an efficient representation of the recorded sound fields. In this paper, we investigate the possible sparse representations of the sound field recorded by multiple microphones in reverberant environments. We combine the Complex Orthogonal Matching Pursuit (COMP) algorithm with the concept of distributed virtual sound sources to propose a sparse sound field representation. The technique uses recordings from a grid of microphones and transforms them into a sparse representation featuring a selected set of active virtual sources. Using simulation, we evaluate the proposed COMP approach with LASSO and IRLS methods in a reverberant room of regular size with a ceiling-mounted microphone array.

Conventional multiple-point active noise control (ANC) systems require placing error microphones within the region of interest (ROI), inconveniencing users. This paper designs a feasible monitoring microphone arrangement placed outside the ROI, providing a user with more freedom of movement. The soundfield within the ROI is interpolated from the microphone signals using a physics-informed neural network (PINN). PINN exploits the acoustic wave equation to assist soundfield interpolation under a limited number of monitoring microphones, and demonstrates better interpolation performance than the spherical harmonics method in simulations. An ANC system is designed to take advantage of the interpolated signal to reduce noise signal within the ROI. The PINN-assisted ANC system reduces noise more than that of the multiple-point ANC system in simulations.

Acoustic velocity vectors (AVVs) are related to the human's perception of sound at low frequencies and are widely used in Ambisonics. This letter proposes a spatial sound field reproduction algorithm called velocity matching, which reproduces the AVVs in the spherical listening region by matching the AVVs' spherical harmonic coefficients. Using the sound field translation formula, the spherical harmonic coefficients of the AVVs are derived from the spherical harmonic coefficients of the pressure, which can be measured by a higher-order microphone array. Unlike algorithms that only control the AVVs at discrete sweet spots, the proposed velocity matching algorithm manipulates the AVVs in the whole spherical listening region and allows the listener to move beyond the sweet spots. Simulations show the proposed velocity matching algorithm accurately reproduces the AVVs in the spherical listening region and requires fewer number of loudspeakers than pressure matching algorithm.

The development of spherical sector harmonics benefits the sound- field decomposition and analysis over a spherical sector region. However, research on the soundfield radial extrapolation from one spherical sector region to another concentric sector region with a different radius is still insufficient. This paper presents a radial extrapolation method for spherical sector soundfields. Based on the extrapolation error and error sensitivity ratio, the performance and robustness of the proposed method is analyzed with different setups. Results show that the proposed method can achieve good performance, especially with a dual array sensor placement, a large angle range of the measurement region, and a small wave number.

Blind source separation aims to recover a series of unmixed signals from only a mixture recording of source signals. For the mixture of speech signals where sources have unique spatial positions, the relative transfer function has been found useful as it contains the spatial information of each source regardless of its signal. In this paper, we transfer a previous relative transfer function based separation method into the wave domain by utilizing a higher-order microphone for the mixture recording. Consequently, the higher-order microphone enables the processing with relative harmonic coefficients, which provides better independency between different coefficient components than the conventional relative transfer functions in each time frame. We demonstrate that the proposed method using relative harmonic coefficients outperforms the relative transfer function based method in highly reverberant rooms through simulation with both simulated and real measured room impulse response data.

Spatial active noise control (ANC) aims to reduce unwanted acoustic noise over a continuous spatial region by generating an anti-noise field with secondary loudspeakers. Conventionally, spatial ANC is achieved by using complex error microphone arrays such as grid or spherical geometry, which are impractical and obstruct the users to enter the quiet region. Recently, a spatial ANC system using circular arrays of microphones has been proposed such that the lower hemisphere of the region of interest is free of microphones for user’s head movement. In this structure, however, the error microphone located at the center of the region (the origin) blocks the head from moving up. In this paper, we optimize the aforementioned system in terms of the error microphone geometry. We remove the requirement to have a microphone at the origin by introducing a single-channel remote microphone technique to the spatial ANC system. Through real-world experiments, we demonstrate that the proposed method achieves noise reduction over space with a more user-friendly error microphone array design.

This paper presents the image source method for simulating the observed signals in the time-domain on the boundary of a spherical listening region. A wideband approach is used where all derivations are in the time-domain. The source emits a sequence of spherical wave fronts whose amplitudes could be related to the far-field directional impulse responses of a loudspeaker. Geometric methods are extensively used to model the observed signals. The spherical harmonic coefficients of the observed signals are also derived.

This paper presents the time-domain wideband spherical microphone array impulse response generator (TDW-SMIR generator), which is a time-domain wideband image source method (ISM) for generating the room impulse responses captured by an open spherical microphone array. To incorporate loudspeaker directivity, the TDW-SMIR generator considers a source that emits a sequence of spherical wave fronts whose amplitudes are related to the loudspeaker directional impulse responses measured in the far-field. The TDW-SMIR generator uses geometric models to derive the time-domain signals recorded by the spherical microphone array. Comparisons are made with frequency-domain single band ISMs. Simulation results prove the results of the TDW-SMIR generator are similar to those of frequency-domain single band ISMs.

Spatial active noise control (ANC) aims to reduce unwanted acoustic noise over a continuous spatial region by generating an anti-noise field with secondary loudspeakers. Conventionally, spatial ANC is achieved by using complex error microphone arrays such as grid or spherical geometry, which are impractical and obstruct the users to enter the quiet region. Recently, the remote microphone technique has been introduced to spatial ANC systems without using error microphones inside the region of interest. However, this technique still requires an error microphone array during the tuning stage. In this paper, we further improve the remote microphone technique by introducing a spatial sound field recording method with a moving higher order microphone for the noise field recording (tuning stage) as well as secondary channel estimations (control stage). This eliminates the requirement for impractical microphone array geometries, typically required in existing spatial ANC solutions. The experimental data based simulation demonstrates the effectiveness of the proposed method on noise reduction over space with its feasible array design.

Direction-of-arrival (DOA) estimation for multiple simultaneous speakers in reverberant environments is still one of the challenging tasks in the audio signal processing field. A recent approach addresses this problem using a spherical harmonics domain feature namedrelative harmonic coefficients(RHC). Based on a bin-wise operation across the STFT (short-time Fourier transform) domain, this method detects the direct-path RHC in the first stage, followed by single source localization in the second stage. However, the method is computationally expensive as each STFT bin requires an exhaustive grid search over the two-dimensional (2-D) directional space. In this paper, we propose a significantly more computationally efficient alternative that decouples the azimuth and elevation 2-D search to two separate one-dimensional (1-D) search. The proposed multi-speaker localization algorithm comprises of two main steps, responsible for: (i) achieving a joint direct-path RHC detection and decoupled DOA estimation using 1-D search; and (ii) counting the number of speakers and estimating their DOAs based on the estimates from direct-path dominated STFT bins. Experiments using both simulated and real-life reverberant recordings confirm the significant computational complexity reduction while achieving competitive localization accuracy, compared to the baseline approaches. Although our proposed method performs in an unsupervised manner, it proves to be applicable even under unfavorable acoustic environments with a high reverberation level (e.g.,$T_{60}=1$second).

This paper presents a sound source localization method using an irregular microphone array embedded in a drone. Sound source localization is an integral function of drone audition systems which enables various applications of drones such as search and rescue missions. However, the audio recordings using the on-board microphones obscure the sound emitted by a source on the ground due to drone generated motor and propeller noise, thus leading to an extremely low signal-to-drone noise ratio (SdNR). In this paper, we propose a cross-correlation based direction of arrival (DOA) estimation technique using the time difference of arrival (TDOA) at different microphone pairs, with noise angular spectrum subtraction. Through the measured current-specific drone noise spectrum, noise suppression has been achieved from the multi-channel recordings. Experimental results show that the proposed method is capable of estimating the position in three-dimensional space for simultaneously active multiple sound sources on the ground at low SdNR conditions ($-30$dB), and localize two sound sources located at a certain azimuth angular separation with low prediction error comparable to the multiple signal classification (MUSIC) based algorithms and the generalized cross-correlation with phase transformation (GCC-PHAT) method. Due to its simplicity, applicability to any array geometry, and better robustness against drone noise, the proposed method increases the feasibility of localization under extreme SdNR levels.

Microphone array calibration is required to accurately capture the information in an audio source recording. Existing calibration methods require expensive hardware and setup procedures to compute filters for correcting microphone responses. Typically, such methods struggle to extend measurement accuracy to low frequencies. As a result, the error due to microphone gain mismatch propagates to all the modes in the spherical harmonic domain representation of a signal. Several existing algorithms use modal representation of sound and error propagation in modes fundamentally limits the performance of such algorithms. A method for reducing the error propagation in modes by correcting the mismatched microphone gains is proposed, where RAndom PerturbatIons for Diffuse-field (RAPID) is used to design filters for correcting the mismatch. Experimental results show that the directivity pattern of a calibrated spherical microphone array using RAPID provides up to 6dB improvement in the front back factor.

A spherical harmonics domain source feature called relative harmonic coefficients (RHC) has recently been applied to address the source direction-of-arrival (DOA) estimation problem. This paper presents a compact evaluation and comparison between two existing RHC based DOA estimators: (i) a method using a full grid search over the two-dimensional (2-D) directional space, (ii) a decoupled estimator which uses one-dimensional (1-D) search to separately localize the source's elevation and azimuth. We also propose a new estimator using a gradient descent search over the 2-D directional grid space. Extensive experiments in both simulated and real-life environments are conducted to examine and analyze the performance of all the underlying DOA estimators. Two objective metrics, including localization accuracy and algorithm complexity, are adopted for an evaluation and comparison between all estimators.

Sound intensity is a good predictor of human perception of sound location, which can be controlled to provide impressive direction perception to humans in soundfield reproduction systems, especially when the loudspeakers are non-uniformly distributed. However, the previous works in this field are all constrained to a single sweet spot/spatial zone. We address this challenge and propose a multizone reproduction method for 3D soundfield in a reverberant room based on intensity matching. We develop spatial sound intensity expressions in a reververant room using spherical harmonic decomposition, and build a cost function to optimize sound intensity within multiple spatial zones. Finally, simulation results showing the performance are presented.

Non-interactive and linear experienceslike cinema film offer high quality surround sound audio to enhance immersion, however, the perspective is usually fixed to the recording microphone position. With the rise of virtual reality, there is a demand for recording and recreating real-world experiences that allow users to move throughout the reproduction. Sound field translation achieves this by building an equivalent environment of virtual sources to recreate the recording spatially. However, the technique remains to restrict the maximum distance a user can translate away from the recording microphone's perspective due to the discrete sampling by commercial higher order microphones only being capable of recording an acoustic sweet-spot. In this paper, we propose a method for binaurally reproducing a microphone recording in a virtual application that allows the user to freely translate their body further beyond the recording position. The method incorporates a mixture of near-field and far-field sources in a sparsely expanded virtual environment to maintain a perceptually accurate reproduction. We perceptually validate the method through a Multiple Stimulus with Hidden Reference and Anchor (MUSHRA) experiment. Compared to the planewave benchmark, the proposed method offers both improved source localizability and robustness to spectral distortions at translated listening positions. A cross-examination with numerical simulations demonstrated that the sparse expansion relaxes the inherent sweet-spot constraint, leading to the improved localizability for sparse environments. Additionally, the proposed method is seen to better reproduce the intensity and binaural room impulse response spectra of near-field environments, further supporting the perceptual results.

Subspace approach of MUSIC (multiple signal classication) has become one of the most popular multi-source direction of arrival (DOA) estimations due to its easy implementation in practice. However, its localization accuracy is vulnerable to noise. This paper develops a novel MUSIC algorithm, more suitable in noisy environments, using the relative sound pressure measurements of a higher order microphone array. This proposed MUSIC approach is also decomposed into the spherical harmonics domain where a frequency smoothing technique is allowed to de-correlate the coherent source signals for improved localization accuracy. The proposed algorithm is also capable of estimating the number of active sound sources, which is pre-requisite knowledge for the traditional MUSIC approach. Extensive experimental results in diverse environments using both simulated and real recordings show advantages of the proposed algorithm over the traditional MUSIC method as well as another recently proposed multi-source localization approach.

Active noise control (ANC) over space is a well-researched topic where multi-microphone, multi-loudspeaker systems are designed to minimize the noise over a spatial region of interest. In this paper, we perform an initial study on the more complex problem of simultaneous noise control over multiple target regions using a single ANC system. In particular, we investigate the maximum active noise control performance over the multiple target regions, given a particular setup of secondary loudspeakers. The performance analysis is carried out using a wave-domain representation to best represent sound propagation over multiple regions in a given enclosure. Furthermore, given the global primary noise field and a fixed secondary source setup, a subspace method is exploited to evaluate the best system performance that could minimize the residual noise fields over multiple regions of interest. We provide experimental results to demonstrate the effectiveness of the proposed method.

We propose a straightforward and cost-effective method to perform diffuse soundfield measurements for calibrating the magnitude response of a microphone array. Typically, such calibration is performed in a diffuse soundfield created in reverberation chambers, an expensive and time-consuming process. A method is proposed for obtaining diffuse field measurements in untreated environments. First, a closed-form expression for the spatial correlation of a wideband signal in a diffuse field is derived. Next, we describe a practical procedure for obtaining the diffuse field response of a microphone array in the presence of a non-diffuse soundfield by the introduction of random perturbations in the microphone location. Experimental spatial correlation data obtained is compared with the theoretical model, confirming that it is possible to obtain diffuse field measurements in untreated environments with relatively few loudspeakers. A 30 second test signal played from 4-8 loudspeakers is shown to be sufficient in obtaining a diffuse field measurement using the proposed method. An Eigenmike®is then successfully calibrated at two different geographical locations.

This paper presents an unsupervised multi-source localization algorithm using a recently introduced feature called the relative harmonic coefficients. We derive a closed-form expression of the feature and briefly summarize its unique properties. We then exploit this feature to develop a single-source frame/bin detector which simplifies the challenging problem of multiple source localization into a single source localization problem. We show that the underlying method is suitable for localization using overlapped, disjoint as well as simultaneous multi-source recordings. Experimental results in both simulated and real-life reverberant environments confirm improved localization accuracy of the proposed method in comparison with the existing state-of-art approach.

Over recent years, spatial acoustic signal processing using higher order microphone arrays in the spherical harmonics domain has been a popular research topic. This paper uses a recently introduced source feature called the relative harmonic coefficients to develop an acoustic signal enhancement approach in noisy environments. This proposed method enables to extract the clean spherical harmonic coefficients from noisy higher order microphone recordings. Hence, this technique can be used as a pre-processing tool for noise-free measurements required by many spatial audio applications. We finally present a simulation study analyzing the performance of this approach in far field noisy environments.

This work presents a method that persuades acoustic reflections to be a favorable property for sound source localization. Whilst most real world spatial audio applications utilize prior knowledge of sound source position, estimating such positions in reverberant environments is still considered to be a difficult problem due to acoustic reflections. This article presents a novel MUSIC framework for multiple sound source localization (range, elevation, azimuth) in reverberant rooms by incorporating a recently proposed region-to-region room transfer model. The method is built upon the received signals of a higher order microphone and a spherical harmonic representation of the room transfer function. We demonstrate the method's general applicability and multiple source localization performance through a simulation study across an assortment of reverberant conditions. Additionally, we investigate robustness against various system modeling errors to gauge implementation viability. Finally, we prove the method in a practical experiment inside a real-world room with measured region-to-region transfer function parameters.

We propose a novel multi-source direction of arrival (DOA) estimation technique using a convolutional neural network algorithm which learns the modal coherence patterns of an incident soundfield through measured spherical harmonic coefficients. We train our model for individual time-frequency bins in the short-time Fourier transform spectrum by analyzing the unique snapshot of modal coherence for each desired direction. The proposed method is capable of estimating simultaneously active multiple sound sources on a 3D space using a single-source training scheme. This single-source training scheme reduces the training time and resource requirements as well as allows the reuse of the same trained model for different multi-source combinations. The method is evaluated against various simulated and practical noisy and reverberant environments with varying acoustic criteria and found to outperform the baseline methods in terms of DOA estimation accuracy. Furthermore, the proposed algorithm allows independent training of azimuth and elevation during a full DOA estimation over 3D space which significantly improves its training efficiency without affecting the overall estimation accuracy.

This article develops a semi-supervised algorithm to address the challenging multi-source localization problem in a noisy and reverberant environment, using a spherical harmonics domain source feature of the relative harmonic coefficients. We present a comprehensive research of this source feature, including (i) an illustration confirming its sole dependence on the source position, (ii) a feature estimator in the presence of noise, (iii) a feature selector exploiting its inherent directivity over space. Source features at varied spherical harmonic modes, representing unique characterization of the soundfield, are fused by the Multi-Mode Gaussian Process modeling. Based on the unifying model, we then formulate the mapping function revealing the underlying relationship between the source feature(s) and position(s) using a Bayesian inference approach. Another issue of the overlapped components is addressed by a pre-processing technique performing overlapped frame detection, which in turn reduces this challenging problem to a single source localization. It is highlighted that this data-driven method has a strong potential to be implemented in practice because only a limited number of labeled measurements is required. We evaluate this proposed algorithm using simulated recordings between multiple speakers in diverse environments, and extensive results confirm improved performance in comparison with the state-of-art methods. Additional assessments using real-life recordings further prove the effectiveness of the method, even at unfavorable circumstances with severe source overlapping.

Active acoustic noise attenuation over a sizable space is a challenging problem in signal processing. The noise attenuation performance of feedforward active noise control (ANC) relies on the preciseness of a reference signal of a primary noise field. To capture the precise reference signal for controlling a sizable space, a large number of reference microphones are required, which reduces system viability. In this study, we exploit an efficient representation of the reference signal in spherical harmonic (SH) domain by utilizing the inherent sparseness of the noise field. The main contributions of this work are as follows. (1) A general reference microphone geometry can be used. The implementation difficulty in the array structure, which is recognized as the common issue of SH-domain signal processing, e.g., use of a fully surrounding spherical array, is reduced by using the fields translation based on the addition theorem. (2) The accuracy of low-frequency signal decomposition is improved. The low accuracy of low-frequency signal decomposition in compressive sensing (CS), which is commonly reported in the literature, is improved by applying signal representation in SH domain. (3) System robustness is increased. The robustness of the system is increased by considering a noise source spatial distribution of both the interior and exterior sound fields, which is not possible in the case of a general signal representation in SH domain. Experimental results indicate that the noise attenuation performance of our proposed method exceeds that of existing solutions. The flexibility of the array structure is also increased, which leads to a more feasible practical system setup.

Spatial active noise control (ANC) systems focus on minimizing unwanted acoustic noise over a continuous spatial region. Conventionally, spatial ANC systems are proposed using point based multi-channel systems and recently novel methods have been developed using spherical harmonic analysis of spatial sound fields. A major limitation for implementing the latter approach is the requirement of regularly distributed microphones and loudspeakers over spherical surfaces. In this paper, we relax the above constraint by constructing a system utilizing multiple circular microphone and loudspeaker arrays and designing a corresponding ANC algorithm. By simulation, we show that the proposed method can achieve comparable ANC performance to conventional spherical array methods. By experiment, we demonstrate the feasibility of implementing the multiple circular array structure and verify its effectiveness given practical constraints.

In literature, particle velocity has been introduced to improve performance of spatial sound field reproduction systems. However, all existing work requires to have accurate particle velocity measurements at all of the discrete control points, which is difficult to obtain in real-world applications. In this work, we formulate continuous particle velocity expressions over space as a function of pressure coefficients in the modal domain that can be easily extracted by using a higher order microphone. The sound field within a target region is controlled by a weighted cost function we built to optimize the continuous particle velocity, as well as sound pressure, on the boundary of the region. In contrast to the conventional spatial sound field reproduction methods in the modal domain, the proposed method allows for non-uniform loudspeaker geometry with a limited number of loudspeakers, thus providing a flexible array arrangement. The performance of the proposed method is evaluated through numerical simulations in both a free field and a reverberant room. Finally, we prove the proposed method in an objective experiment with real-world measurements of room impulse response.

Sound intensity is an acoustic quantity closely linked with human perception of sound location, and it can be controlled to create a high level of realism to humans in soundfield reproduction systems. In this article, we present an intensity matching technique to optimally reproduce sound intensity over a continuous spatial region using an irregular loudspeaker array. This avoids several known limitations in the previous works on intensity based soundfield reproduction, such as a single sweet spot for the listener and a regular loudspeaker geometry that is difficult to implement in real-world applications. In contrast to the previous works, the new technique uses a cost function we built to optimize sound intensity over space by exploiting spatial sound intensity distributions. The spatial sound intensity distribution is represented by spherical harmonic coefficients of sound pressure, which are widely used to describe a spatial soundfield. Compared to the conventional spatial soundfield reproduction method of pressure matching in the spherical harmonic domain and the HOA max-rE decoding method optimizing sound intensity at a single position, we show that the intensity matching technique has better overall performance with two different irregular loudspeaker layouts through simulations. The impact of microphone noise on reproduction performance is also assessed. Finally, we carry out perceptual localization experiments to validate the proposed method.

The localization of acoustic sound sources is beneficial to signal processing applications of speech enhancement, dereverberation, separation and tracking. Difficulties in position estimation arise in real world environments due to coherent reflections degrading performance of subspace localization techniques. This paper proposes a method of multiple signal classification (MUSIC) subspace localization, which is suitable for reverberant rooms. The method is based on the modal decomposition of a room’s region-to-region transfer function, which is assumed to be known. We perform a numerical simulation of four sound sources in a reverberant room, and show that the localization method exhibits increased spatial resolution and distance focusing abilities when the region-to-region transfer function is incorporated. The proposed method is successful in estimating three-dimensional sound source positions without distortion due to reverberation.

The accuracy and perception of soundfields produced by loudspeaker arrays are strongly influenced by the inherent characteristics of the commercial loudspeakers. This paper analyzes such characteristics of loudspeakers by deriving equivalent theoretical models, and by studying their impact on soundfield reproduction. A number of acoustic models are investigated, including plane waves decomposition, point source decomposition and mixed source decomposition. Each proposed model employs three effective sparse decomposition algorithms for optimized solutions, including iteratively reweighted least squares (IRLS), matching pursuit (MP) and least absolute shrinkage and selection operator (LASSO). A successful model shall enable the prediction of the soundfield outside the original recording region. Therefore, we validate the effectiveness of the models by comparing the simulated soundfield with secondary measurements obtained beyond the original area. Experimental results have confirmed that both the plane wave and mixed source model achieve promising performance with respect to the proposed metrics.

Active Noise Cancellation (ANC) is a well researched topic for minimizing unwanted acoustic noise, and spatial ANC is a recently introduced concept that focuses on continuous spatial regions. Adaptive filter designing for spatial ANC is often based on frequency-domain spherical harmonic decomposition method, which has a major limitation due to the increased system latency. In this paper, we develop a time-domain spherical harmonic based signal decomposition method and use it to develop two time-space domain feed-forward adaptive filters for spatial ANC. Through simulations we show that the proposed methods can achieve higher noise reduction performance over the control region with microphones located on the surface of the region compared to the conventional time-domain adaptive filter.

In this paper, we propose a planar array of dipole (or first-order) loudspeakers to reproduce a full three dimensional (3D) exterior soundfield over a desired spatial region. The proposed method is inspired by the spherical harmonics based solution for 3D soundfield reproduction. When decomposed in terms of spherical harmonics, we separate the corresponding soundfield coefficients into two sets (even and odd) and exploit the inherent properties of Legendre polynomials to control each set using a planar array of dipole (or first-order) speakers. We provide simulation examples to demonstrate the performance of the proposed method.

We proposed a spatial coherence-based PSD estimation and source separation technique in [1] using a 32-channel spherical microphone array. While the proposed spherical microphone-based method exhibited a satisfactory performance in separating multiple sound sources in a reverberant environment, the use of a large number of microphones remains an issue for some practical considerations. In this paper, we investigate an alternative array structure to achieve spatial coherence-based source separation using a planar microphone array. This method is particularly useful in separating a limited number of sound sources in a mixed acoustic scene. The simplified array structure we used here can easily be integrated with many commercial acoustical instruments such as smart home devices to achieve better speech enhancements.

In this paper, we propose an efficient technique for estimating individual power spectral density (PSD) components, i.e., PSD of each desired sound source as well as of noise and reverberation, in a multisource reverberant sound scene with coherent background noise. We formulate the problem in the spherical harmonics domain to take the advantage of the inherent orthogonality of the spherical harmonics basis functions and extract the PSD components from the cross-correlation between the different sound field modes. We also investigate an implementation issue that occurs at the nulls of the Bessel functions and offer an engineering solution. The performance evaluation takes place in a practical environment with a commercial microphone array in order to measure the robustness of the proposed algorithm against all the deviations incurred in practice. We also exhibit an application of the proposed PSD estimator through a source septation algorithm and compare the performance with a contemporary method in terms of different objective measures.

Noise control and cancellation over a spatial region is a fundamental problem in acoustic signal processing. In this paper, we utilize wave-domain adaptive algorithms to iteratively calculate the secondary source driving signals and to cancel the primary noise field over the control region. We propose wave-domain active noise control algorithms based on two minimization problems: first, minimizing the wave-domain residual signal coefficients, and second, minimizing the acoustic potential energy over the region, and derive the update equations with respect to two variables, the loudspeaker weights and wave-domain secondary source coefficients. Simulation results demonstrate the effectiveness of the proposed algorithms, more specifically the convergence speed and the noise cancellation performance in terms of the noise reduction level and acoustic potential energy reduction level over the entire spatial region.

This paper presents an experimental study on a novel technique to blindly estimate the directional properties of room reflections using a spherical microphone array. The algorithm is developed based on a spatial correlation model formulated in the spherical harmonics domain. This model expresses the cross correlation matrix of the recorded soundfield coefficients in terms of direct sound and reflections. The directional gain of the reflected path is estimated from the above model, which provides information on the DOAs of dominant wall reflections. The practical feasibility of the proposed algorithm is evaluated using a subset of the speech corpus from the ACE (Acoustic Characterization of Environments) Challenge.

The direct-to-reverberant ratio (DRR) is an important characterization of a reverberant environment. This paper presents a novel blind DRR estimation method based on the coherence function between the sound pressure and particle velocity at a point. First, a general expression of coherence function and DRR is derived in the spherical harmonic domain, without imposing assumptions on the reverberation. In this paper, DRR is expressed in terms of the coherence function as well as two parameters that are related to statistical characteristics of the reverberant environment. Then, a method to estimate the values of these two parameters using a microphone system capable of capturing first-order spherical harmonics is proposed, under three assumptions which are more realistic than the diffuse field model. Furthermore, a theoretical analysis on the use of plane wave model for direct path signal and its effect on DRR estimation is presented, and a rule of thumb is provided for determining whether the point source model should be used for the direct path signal. Finally, the ACE challenge dataset is used to validate the proposed DRR estimation method. The results show that the average full band estimation error is within 2 dB, with no clear trend of bias.

The direct-to-reverberant ratio (DRR), which describes the energy ratio between the direct and reverberant component of a soundfield, is an important parameter in many audio applications. In this paper, we present a multichannel algorithm, which utilizes the blind recordings of a spherical microphone array to estimate the DRR of interest. The algorithm is developed based on a spatial correlation model formulated in the spherical harmonics domain. This model expresses the cross correlation matrix of the recorded soundfield coefficients in terms of two spatial correlation matrices, one for direct sound and the other for reverberation. While the direct path arrives from the source, the reverberant path is considered to be a nondiffuse soundfield with varying directional gains. The direct and reverberant sound energies are estimated from the aforementioned spatial correlation model, which then leads to the DRR estimation. The practical feasibility of the proposed algorithm was evaluated using the speech corpus of the acoustic characterization of environments challenge. The experimental results revealed that the proposed method was able to effectively estimate the DRR of a large collection of reverberant speech recordings including various environmental noise types, room types and speakers.

In this paper, we investigate active noise control over large 2D spatial regions when the noise source is sparsely distributed. The l1relaxation technique originated from compressive sensing is adopted and based on that we develop the algorithm for two cases: multipoint noise cancellation and wave domain noise cancellation. This results in two new variants (i) zero-attracting multi-point complex FxLMS and (ii) zero-attracting wave domain complex FxLMS. Both approaches use a feedback control system, where a microphone array is distributed over the boundary of the control region to measure the residual noise signals and a loudspeaker array is placed outside the microphone array to generate the anti-noise signals. Simulation results demonstrate the performance and advantages of the proposed methods in terms of convergence rate and spatial noise reduction levels.

This paper proposes an efficient parameterization of the room transfer function (RTF). Typically, the RTF rapidly varies with varying source and receiver positions, hence requires an impractical number of point to point measurements to characterize a given room. Therefore, we derive a novel RTF parameterization that is robust to both receiver and source variations with the following salient features: 1) The parameterization is given in terms of a modal expansion of 3D basis functions. 2) The aforementioned modal expansion can be truncated at a finite number of modes given that the source and receiver locations are from two sizeable spatial regions, which are arbitrarily distributed. 3) The parameter weights/coefficients are independent of the source/receiver positions. Therefore, a finite set of coefficients is shown to be capable of accurately calculating the RTF between any two arbitrary points from a pre-defined spatial region where the source(s) lie and a pre-defined spatial region where the receiver(s) lie. A practical method to measure the RTF coefficients is also provided, which only requires a single microphone unit and a single loudspeaker unit, given that the room characteristics remain stationary over time. The accuracy of the above parameterization is verified using appropriate simulation examples.

Successful recording of large spatial soundfields is a prevailing challenge in acoustic signal processing due to the enormous numbers of microphones required. This paper presents the design and analysis of an array of higher order microphones that uses 2D wavefield translation to provide a mode matching solution to the height invariant recording problem. It is shown that the use of Mth order microphones significantly reduces the number of microphone units by a factor of 1/(2M + 1) at the expense of increased complexity at each microphone unit. Robustness of the proposed array is also analyzed based on the condition number of the translation matrix while discussing array configurations that result in low condition numbers. The white-noise gain (WNG) of the array is then derived to verify that improved WNG can be achieved when the translation matrix is well conditioned. Furthermore, the array's performance is studied for interior soundfield recording as well as exterior soundfield recording using appropriate simulation examples.

Three dimensional surround sound reproduction over large areas is a prevailing challenge due to the enormous numbers of loudspeakers required. In this paper, we propose an array of higher order loudspeakers which provide a mode matching solution to the problem based on 3D wavefield translation. It is shown that for a given bandwidth, the use of Lthorder sources significantly brings down the minimum loudspeaker requirement by a factor of 1=(L + 1)2. Furthermore, the array is shown to be capable of exterior field cancellation, increasing its performance in echoing environments. Design examples are given for interior field, exterior field and interior and exterior combined field reproduction.