Active control of sound inside a sphere via control of the acoustic pressure at the boundary surface

Here we investigate the practical feasibility of performing soundfield reproduction throughout a three-dimensional area by controlling the acoustic pressure measured at the boundary surface of the volume in question. The main aim is to obtain quantitative data showing what performances a practical implementation of this strategy is likely to yield. In particular, the influence of two main limitations is studied, namely the spatial aliasing and the resonance problems occurring at the eigenfrequencies associated with the internal Dirichlet problem. The strategy studied is first approached by performing numerical simulations, and then in experiments involving active noise cancellation inside a sphere in an anechoic environment. The results show that noise can be efficiently cancelled everywhere inside the sphere in a wide frequency range, in the case of both pure tones and broadband noise, including cases where the wavelength is similar to the diameter of the sphere. Excellent agreement was observed between the results of the simulations and the measurements. This method can be expected to yield similar performances when it is used to reproduce soundfields.Comment: 28 pages de text

Surround by Sound: A Review of Spatial Audio Recording and Reproduction

In this article, a systematic overview of various recording and reproduction techniques for spatial audio is presented. While binaural recording and rendering is designed to resemble the human two-ear auditory system and reproduce sounds specifically for a listener’s two ears, soundfield recording and reproduction using a large number of microphones and loudspeakers replicate an acoustic scene within a region. These two fundamentally different types of techniques are discussed in the paper. A recent popular area, multi-zone reproduction, is also briefly reviewed in the paper. The paper is concluded with a discussion of the current state of the field and open problemsThe authors acknowledge National Natural Science Foundation of China (NSFC) No. 61671380 and Australian Research Council Discovery Scheme DE 150100363

Spatial dissection of a soundfield using spherical harmonic decomposition

A real-world soundfield is often contributed by multiple desired and undesired sound sources. The performance of many acoustic systems such as automatic speech recognition, audio surveillance, and teleconference relies on its ability to extract the desired sound components in such a mixed environment. The existing solutions to the above problem are constrained by various fundamental limitations and require to enforce different priors depending on the acoustic condition such as reverberation and spatial distribution of sound sources. With the growing emphasis and integration of audio applications in diverse technologies such as smart home and virtual reality appliances, it is imperative to advance the source separation technology in order to overcome the limitations of the traditional approaches. To that end, we exploit the harmonic decomposition model to dissect a mixed soundfield into its underlying desired and undesired components based on source and signal characteristics. By analysing the spatial projection of a soundfield, we achieve multiple outcomes such as (i) soundfield separation with respect to distinct source regions, (ii) source separation in a mixed soundfield using modal coherence model, and (iii) direction of arrival (DOA) estimation of multiple overlapping sound sources through pattern recognition of the modal coherence of a soundfield. We first employ an array of higher order microphones for soundfield separation in order to reduce hardware requirement and implementation complexity. Subsequently, we develop novel mathematical models for modal coherence of noisy and reverberant soundfields that facilitate convenient ways for estimating DOA and power spectral densities leading to robust source separation algorithms. The modal domain approach to the soundfield/source separation allows us to circumvent several practical limitations of the existing techniques and enhance the performance and robustness of the system. The proposed methods are presented with several practical applications and performance evaluations using simulated and real-life dataset

Spatial Acoustic Vector Based Sound Field Reproduction

Spatial sound field reproduction aims to recreate an immersive sound field over a spatial region. The existing sound pressure based approaches to spatial sound field reproduction focus on the accurate approximation of original sound pressure over space, which ignores the perceptual accuracy of the reproduced sound field. The acoustic vectors of particle velocity and sound intensity appear to be closely linked with human perception of sound localization in literature. Therefore, in this thesis, we explore the spatial distributions of the acoustic vectors, and seek to develop algorithms to perceptually reproduce the original sound field over a continuous spatial region based on the vectors. A theory of spatial acoustic vectors is first developed, where the spatial distributions of particle velocity and sound intensity are derived from sound pressure. To extract the desired sound pressure from a mixed sound field environment, a 3D sound field separation technique is also formulated. Based on this theory, a series of reproduction techniques are proposed to improve the perceptual performance. The outcomes resulting from this theory are: (i) derivation of a particle velocity assisted 3D sound field reproduction technique which allows for non-uniform loudspeaker geometry with a limited number of loudspeakers, (ii) design of particle velocity based mixed-source sound field translation technique for binaural reproduction that can provide sound field translation with good perceptual experience over a large space, (iii) derivation of an intensity matching technique that can reproduce the desired sound field in a spherical region by controlling the sound intensity on the surface of the region, and (iv) two intensity based multizone sound field reproduction algorithms that can reproduce the desired sound field over multiple spatial zones. Finally, these techniques are evaluated by comparing to the conventional approaches through numerical simulations and real-world experiments

Extraction of exterior field from a mixed sound field for 2D height-invariant sound propagation

Any sound field caused by one or more sound sources takes the form of an interior, exterior or a mixed sound field based on the source locations. The recording and reproduction of interior or exterior sound fields in terms of harmonic decomposition has been extensively studied in the literature, however the challenging task of separating them in a mixed field remains largely unexplored. But in nature, the interior and exterior sound fields often co-exist, hence their isolation can be very useful in many acoustic processes. In this paper, we discuss a method to extract the exterior field from a mixed sound field for 2D height-invariant sound propagation. Such an extraction method can be employed to record a sound field in a noisy or interfered room or to perform dereverberation in a reverberant room where the sound fields due to the source signal and its reflections superimpose each other. We demonstrate two practical uses of the proposed method in the forms of (i) an exterior sound field recording in a mixed wave field and (ii) speech dereverberation in a simulated reverberant roomThis work is supported by Australian Research Council (ARC) Discovery Projects funding scheme (project no. DP140103412)

EigenScape : A Database of Spatial Acoustic Scene Recordings

The classification of acoustic scenes and events is an emerging area of research in the field of machine listening. Most of the research conducted so far uses spectral features extracted from monaural or stereophonic audio rather than spatial features extracted from multichannel recordings. This is partly due to the lack thus far of a substantial body of spatial recordings of acoustic scenes. This paper formally introduces EigenScape, a new database of fourth-order Ambisonic recordings of eight different acoustic scene classes. The potential applications of a spatial machine listening system are discussed before detailed information on the recording process and dataset are provided. A baseline spatial classification system using directional audio coding (DirAC) techniques is detailed and results from this classifier are presented. The classifier is shown to give good overall scene classification accuracy across the dataset, with 7 of 8 scenes being classified with an accuracy of greater than 60% with an 11% improvement in overall accuracy compared to use of Mel-frequency cepstral coefficient (MFCC) features. Further analysis of the results shows potential improvements to the classifier. It is concluded that the results validate the new database and show that spatial features can characterise acoustic scenes and as such are worthy of further investigatio

3D sound field analysis using circular higher-order microphone array

This paper proposes the theory and design of circular higher-order microphone arrays for 3D sound field analysis using spherical harmonics. Through employing the spherical harmonic translation theorem, the local spatial sound fields recorded by each higher-order microphone placed in the circular arrays are combined to form the sound field information of a large global spherical region. The proposed design reduces the number of the required sampling points and the geometrical complexity of microphone arrays. We develop a two-step method to calculate sound field coefficients using the proposed array structure, i) analytically combine local sound field coefficients on each circular array and ii) solve for global sound field coefficients using data from the first step. Simulation and experimental results show that the proposed array is capable of acquiring the full 3D sound field information over a relatively large spherical region with decent accuracy and computational simplicity.This work was supported under the Australian Research Councils Discovery Projects funding scheme (project no. DP140103412)

Reconstructing the Dynamic Directivity of Unconstrained Speech

This article presents a method for estimating and reconstructing the spatial energy distribution pattern of natural speech, which is crucial for achieving realistic vocal presence in virtual communication settings. The method comprises two stages. First, recordings of speech captured by a real, static microphone array are used to create an egocentric virtual array that tracks the movement of the speaker over time. This virtual array is used to measure and encode the high-resolution directivity pattern of the speech signal as it evolves dynamically with natural speech and movement. In the second stage, the encoded directivity representation is utilized to train a machine learning model that can estimate the full, dynamic directivity pattern given a limited set of speech signals, such as those recorded using the microphones on a head-mounted display. Our results show that neural networks can accurately estimate the full directivity pattern of natural, unconstrained speech from limited information. The proposed method for estimating and reconstructing the spatial energy distribution pattern of natural speech, along with the evaluation of various machine learning models and training paradigms, provides an important contribution to the development of realistic vocal presence in virtual communication settings.Comment: In proceedings of I3DA 2023 - The 2023 International Conference on Immersive and 3D Audio. DOI coming soo