Compressive Spherical Beamforming for Acoustic Source Identification

This paper utilizes a rigid spherical microphone array to reduce wind noise. In the experiments conducted, a loudspeaker is used to reproduce the desired sound signal and an axial fan is employed to generate wind noise in an anechoic chamber. The sound signal and wind noise are measured separately with the spherical microphone array and analyzed in the spherical harmonic domain. The wind noise is found to be irregularly distributed in the spherical harmonic domain, distinct from the sound signal which is concentrated in the first few spherical harmonic modes. This difference is utilized to reduce wind noise without degrading the desired sound pressure level (SPL) by use of a low pass filter method in the spherical harmonic domain. Experimental results with both single-tonal and multi-tonal sound signals demonstrate that the proposed method can reduce wind noise by more than 10 dB in the frequency range below 500 Hz. The SPL of the desired sound signal can be extracted from wind noise with an error within 1.0 dB, even when the sound level is 8 dB lower than wind noise.

Fast direction-of-arrival estimation algorithm for multiple wideband acoustic sources using multiple open spherical arrays

Source localization has been studied in the spatial domain using differential geometry in earlier work. However, parameters of the sensor array manifold have hitherto not been investigated for source localization in spherical harmonics domain. The objective of this work is to represent and model the manifold surface using differential geometry. The system model for source localization over a spherical harmonic manifold is first formulated. Subsequently, the manifold parameters are modeled in the spherical harmonics domain. Source localization methods using MUSIC and MVDR over the spherical harmonics manifold are developed. Experiments on source localization using a spherical microphone array indicate high resolution in noise.

The area of sound field synthesis has significantly advanced in the past decade, facilitated by the development of high-quality sound-field capturing and re-synthesis systems. Spherical microphone arrays are among the most recently developed systems for sound field capturing, enabling processing and analysis of three-dimensional sound fields in the spherical harmonics domain. In spite of these developments, a clear relation between sound fields recorded by spherical microphone arrays and their perception with a re-synthesis system has not yet been established, although some relation to scalar measures of spatial perception was recently presented. This paper presents an experimental study of spatial sound perception with the use of a spherical microphone array for sound recording and headphone-based binaural sound synthesis. Sound field analysis and processing is performed in the spherical harmonics domain with the use of head-related transfer functions and simulated enclosed sound fields. The effect of several factors, such as spherical harmonics order, frequency bandwidth, and spatial sampling, are investigated by applying the repertory grid technique to the results of the experiment, forming a clearer relation between sound-field capture with a spherical microphone array and its perception using binaural synthesis regarding space, frequency, and additional artifacts. The experimental study clearly shows that a source will be perceived more spatially sharp and more externalized when represented by a binaural stimuli reconstructed with a higher spherical harmonics order. This effect is apparent from low spherical harmonics orders. Spatial aliasing, as a result of sound field capturing with a finite number of microphones, introduces unpleasant artifacts which increased with the degree of aliasing error.

The reliable estimation of fiber orientation distributions from diffusion-sensitized magnetic resonance imaging is an important processing step for revealing structural connectivity in the human brain. Fiber orientation distributions are usually represented in spherical harmonic (SH) domain, but many modern spatial regularization techniques were not yet formulated in SH-domain such that they cannot benefit from the well known advantages. In this article we propose a novel SH-formulation of the contour enhancement propagator (fiber continuity) which enables to implement a variety of processing steps in SH-domain.

Open-sphere microphone arrays are preferred over rigid-sphere arrays when minimal interaction between array and the measured sound field is required. However, open-sphere arrays suffer from poor robustness at null frequencies of the spherical Bessel function. This letter proposes a maximum likelihood method for direction of arrival estimation in the spherical harmonic domain, which avoids the division of the spherical Bessel function and can be used at arbitrary frequencies. Furthermore, the method can be easily extended to wideband implementation. Simulation and experiment results demonstrate the superiority of the proposed method over the commonly used methods in open-sphere configurations.

Estimation of the direction of arrival (DOA) of reflections in a room using spherical microphone arrays can be performed using several methods such as plane-wave decomposition, and delay-and-sum beamforming, for which the resolution of the estimation process is usually bounded by the array order, or the number of microphones. In this paper a method for DOA estimation of the reflections in a room using room impulse-response data and spherical microphone arrays is presented, in which only a first order microphone array is required. The proposed method uses signal processing in the spherical harmonics domain, utilizing an analytical dependence of the spherical harmonic coefficients on different acoustics parameters. It is shown that the zero order spherical harmonics coefficients is a function of the time delays and amplitudes of the planes waves composing the sound field, while the first order coefficients are a function of the time delays, amplitudes and the elevation and azimuth components of the wave arrival direction. Using this property leads to the development of an estimator based on the least-squares approach, in which each order is used to estimate a single sound-field parameter.

Spherical array plays important role in 3D targets localization. In this paper, we develop a novel DOA estimation method for the spherical array with super resolution approach. The proposed method operates in spherical harmonic domain. Based on the atomic norm minimization, we develop a gridless L1-SVD algorithm in spherical harmonic domain and then we adopt the spherical ESPRIT method to two-dimensional DOA estimation. Compared to the previous work, the proposed method acquires better estimation performance. Numerical simulation results verify the performance of the proposed method.

A constrained Kalman beamforming (CKB) method in spherical harmonics domain is proposed to localize multiple sources captured by spherical arrays. It scans the Euclidean norm of the weights in three-dimensional space to estimate source directions. It can improve the accuracy of sound source localization when steering vector mismatch exits. Moreover, it has the advantage of rapid convergence and online implementation. Compared with the desired minimum variance distortionless response (MVDR) and diagonal loading (DL) methods, simulation results show that the proposed algorithm has robustness to arbitrary steering vector mismatch and low number of snapshots.

A recent and fast evolving application for microphone arrays is the auditory systems of humanoid robots. These arrays, in contrast to conventional arrays, are not fixed in a given position, but move together with the robot. While imposing a challenge to most conventional array processing algorithms, this movement offers an opportunity to enhance performance if utilized in an appropriate manner. The array movement can increase the amount of information gathered and, therefore, improve various aspects of array processing. This paper presents a theoretical framework for the processing of moving microphone arrays for humanoid robot audition based on a representation of the surrounding sound field in the spherical harmonics domain. A simulation study is provided, illustrating the use and the potential advantage of the proposed framework.

Reproduction of high quality spatial sound has gained considerable importance with the recent technology developments in the fields of virtual and augmented reality. Recently, the reproduction of binaural signals in the Spherical-Harmonics (SH) domain has been proposed. This is performed by using SH representations of the sound-field and the Head-Related Transfer Function (HRTF). These processes offer the flexibility to control the reproduced binaural signals, by manipulating the sound-field or the HRTFs using algorithms that operate directly in the SH domain. However, in most practical cases, the binaural reproduction is order-limited, which introduces truncation error that has a detrimental effect on the perception of the reproduced signals, mainly due to the truncation of the HRTF. A recent study showed that pre-processing of the HRTF by ear-alignment reduces its effective SH order, which may be beneficial for alleviating the above effect. In this paper, a method to incorporate the pre-processed ear-aligned HRTF into the binaural reproduction process is presented. The method uses Ambisonics representation of the sound-field formulated at the two ears, and is denoted here as Bilateral Ambisonics. The proposed method leads to a significant reduction in errors due to the limited-order reproduction, which yields a substantial improvement in perceived binaural reproduction quality even with SH as low as first order.

This paper concerns the problem of convolutive sound source separation from mutlichannel recordings made with a spherical microphone array. In particular, we formulate two state-of-the-art separation techniques based on Expectation Maximization (EM) and Nonnegative Tensor Factorization (NTF) in the spherical harmonic domain (SHD). Furthermore, we adjust and incorporate the Gaussian Localization Prior (GLP) to the proposed algorithms, which yields two variants of the derived methods. For the source signal reconstruction, a Minimum Variance Distortionless Response (MVDR) beamformer with a single-channel Wiener post-filter is employed. The performance comparison is based on experimental evaluation using micro-phone signals simulated with the image-source method in several scenarios, including diverse geometrical setup, different number of sources and various types of source signals, namely the recordings of speech utterances and musical instruments. The experimental results for the first-order ambisonic signals show that the proposed methods enable high-quality sound source separation in the spherical harmonic domain. In particular, we show that incorporation of the Gaussian Localization Prior to the proposed algorithms leads to a substantial improvement in separation performance.

Separation of coincident speech sources using microphone arrays is a challenging problem. Radial filters can be designed in the spherical harmonic domain to separate coincident speech sources effectively. Limited studies have been conducted on polynomial based near-field radial filter design in the spherical harmonic domain earlier. In this paper, a radial filter design method using a frequency domain Kaiser window function is proposed. The magnitude response of the Kaiser window function exhibits sharp notches, making it a good candidate for the design of radial notch filters. The polynomial expansion of the Kaiser window can be utilized for modeling the spherical array beamformer output. Improved white noise gain and directivity index are noted in the radial filters designed using the Kaiser window function. The radial filter is also used to separate co-incident speech sources. Experimental results on coincident speech source separation indicate better LSD, PESQ, and SDR scores than existing approaches.

Microphone arrays are used in speech signal processing applications such as teleconferencing and telepresence, in order to enhance a desired speech signal in the presence of speech signals from other speakers, reverberation and background noise. These arrays usually provide a single-channel output, so that no spatial information is available in the output signal. However, spatial information on the sound sources may increase the intelligibility of a speech signal perceived by a human listener. This work presents a mathematical framework for generalized spherical array beamforming that in addition to suppressing noise and reverberation, is aiming to preserve spatial information on the sources in the recording venue. The generalized beamforming, formulated in the spherical harmonics domain, is based on binaural sound reproduction where the head-related transfer functions are incorporated into a headphones presentation. The performance of the proposed generalized beamformer is compared to that of a single-channel output maximum-directivity beamformer. Listening tests with human subjects show that when the generalized beamformer is used the intelligibility is improved at low input SNRs.

Directional room impulse responses (DRIR) measured with spherical microphone arrays (SMA) enable the reproduction of room reverberation effects on three-dimensional surround-sound systems (e.g., Higher-Order Ambisonics) through multichannel convolution. However, such measurements inevitably contain a nondecaying noise floor that may produce an audible “infinite reverberation effect” upon convolution. If the late reverberation tail can be considered a diffuse field before reaching the noise floor, the latter may be removed and replaced with an extension of the exponentially-decaying tail synthesized as a zero-mean Gaussian noise. This has previously been shown to preserve the diffuse-field properties of the late reverberation tail when performed in the spherical harmonic domain (SHD). In this paper, we show that in the case of highly anisotropic yet incoherent late fields, the spatial symmetry of the spherical harmonics is not conducive to preserving the energy distribution of the reverberation tail. To remedy this, we propose denoising in an optimized spatial domain obtained by plane-wave decomposition (PWD), and demonstrate that this method equally preserves the incoherence of the late reverberation field.