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

Chen, Hanchi; Abhayapala, Thushara D.; Zhang, Wen

doi:10.1109/eusipco.2015.7362564

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…Samarasinghe et al [15] developed a regularized leastsquares inverse interpolation approach based on spherical harmonic translation coefficients using an array of HOA microphones. Several subsequent studies have demonstrated or improved upon this method [16][17][18]. In particular, Ueno et al [19] developed a similar method that takes a Bayesian inference approach, which was shown to achieve improved performance (in terms of reconstruction errors) at high frequencies.…”

Section: Linear Methodsmentioning

confidence: 99%

Fundamentals of a Parametric Method for Virtual Navigation Within an Array of Ambisonics Microphones

Tylka¹,

Choueiri²

2020

J. Audio Eng. Soc.

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Fundamental aspects of a method for virtual navigation of a sound field within an array of ambisonics microphones, wherein the subset of microphones to be used for interpolation is determined parametrically, are presented. An existing, weighted-average-based navigational method serves as a benchmark due to its simplicity and its applicability to arbitrary sound fields but introduces comb-filtering and, for near-field sources, degrades localization. A critical review of existing methods is presented, through which a number of issues are identified. In the proposed method, those microphones that are nearer to the desired listening position than to any source are determined based on the known or inferred positions of sources. The signals from only those microphones are then interpolated using a regularized least-squares matrix of filters. Spectral distortions and source localization errors are characterized for the benchmark and proposed methods via numerical simulations of a two-microphone array, and an experimental validation of these simulations is presented. Results show that, for near-field sources, the proposed method significantly outperforms the benchmark in both spectral and localization accuracy due to the exclusion of the second microphone. For far-field sources, the proposed method achieves slightly decreased spectral distortions due to the flattened response of the interpolation filters.

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Section: Linear Methodsmentioning

confidence: 99%

Fundamentals of a Parametric Method for Virtual Navigation Within an Array of Ambisonics Microphones

Tylka¹,

Choueiri²

2020

J. Audio Eng. Soc.

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show abstract

“…Approaches based on HOA representations include extrapolation-based algorithms [6][7][8][9][10], which extrapolate a finite set of spatial parameters based on measured RIRs and thus allow the RIR to be synthesized outside the region covered by microphones. While such extrapolation approaches can introduce inaccurate source localization and audible processing artifacts, such as spectral coloration [11], a number of interpolation-based approaches using HOA microphone array recordings are prone to mitigate these effects, such as the regularized least-squares interpolation approaches using spherical harmonic translation coefficients [12][13][14][15]. More recent related work [16,17] utilized frequency-dependent regularization to limit spectral variation and exclude any microphones closer to a sound source than to the target listening position in order to obtain accurate results for near-field sources.…”

Section: Introductionmentioning

confidence: 99%

Interpolating the Directional Room Impulse Response for Dynamic Spatial Audio Reproduction

et al. 2022

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Virtual reality (VR) is increasingly important for exploring the real world, which has partially moved to virtual workplaces. In order to create immersive presence in a simulated scene for humans, VR needs to reproduce spatial audio that describes three-dimensional acoustic characteristics in the counterpart physical environment. When the user moves, this reproduction should be dynamically updated, which provides practical challenges because the bandwidth for continuously transmitting audio and video scene data may be limited. This paper proposes an interpolation approach for dynamic spatial audio reproduction using acoustic characteristics of direction and reverberation at limited numbers of positions, which are represented using a first order Ambisonics encoding of the room impulse response (RIR), called the directional RIR (DRIR). We decompose two known DRIRs into reflection components, before interpolating early dominant components for DRIR synthesis and utilizing DRIR recordings for accuracy evaluation. Results indicate that the most accurate interpolation is obtained by the proposed method over two comparative approaches, particularly in a simulated small room where most direction of arrival estimation errors of early components are below five degrees. These findings suggest precise interpolated DRIRs with limited data using the proposed approach, which is vital for dynamic spatial audio reproduction for VR applications.

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Estimation of spherical harmonic coefficients in sound field recording using feed-forward neural networks

Zhang

Wang

et al. 2020

Multimed Tools Appl

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

Cited by 5 publications

References 12 publications

Fundamentals of a Parametric Method for Virtual Navigation Within an Array of Ambisonics Microphones

Fundamentals of a Parametric Method for Virtual Navigation Within an Array of Ambisonics Microphones

Interpolating the Directional Room Impulse Response for Dynamic Spatial Audio Reproduction

Estimation of spherical harmonic coefficients in sound field recording using feed-forward neural networks

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