Spatial Encoding of Finite Difference Time Domain Acoustic Models for Auralization

Southern, Alex; Murphy, Damian; Savioja, Lauri

doi:10.1109/tasl.2012.2203806

Cited by 12 publications

(13 citation statements)

References 8 publications

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“…The black circle displayed in the figure represents the area of accurate reconstruction predicted by solving Equation 14for R. indicates that the region in which the reconstruction is accurate increases when a higher number of uniformly-distributed plane waves is considered in the expansion. Good agreement was found between the radius predicted by Equation (14) and the area where the reconstruction is correct. A preliminary analysis was performed to establish the size of the microphone array and the number of plane waves required to generate an inverse matrix whose condition number is smaller than 10 6 .…”

Section: Plane Wave Expansion From Finite Element Datamentioning

confidence: 62%

“…Translation and rotation of the acoustic field can be then achieved by the application of mathematical operators. Southern et al [14] proposed a method to obtain a spherical harmonic representation of FDTD simulations. The approach uses the the Blumlein difference technique to create a higher order directivity pattern from two adjacent lower orders.…”

Section: Introductionmentioning

confidence: 99%

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Low Frequency Interactive Auralization Based on a Plane Wave Expansion

2017

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This paper addresses the problem of interactive auralization of enclosures based on a finite superposition of plane waves. For this, room acoustic simulations are performed using the Finite Element (FE) method. From the FE solution, a virtual microphone array is created and an inverse method is implemented to estimate the complex amplitudes of the plane waves. The effects of Tikhonov regularization are also considered in the formulation of the inverse problem, which leads to a more efficient solution in terms of the energy used to reconstruct the acoustic field. Based on this sound field representation, translation and rotation operators are derived enabling the listener to move within the enclosure and listen to the changes in the acoustic field. An implementation of an auralization system based on the proposed methodology is presented. The results suggest that the plane wave expansion is a suitable approach to synthesize sound fields. Its advantage lies in the possibility that it offers to implement several sound reproduction techniques for auralization applications. Furthermore, features such as translation and rotation of the acoustic field make it convenient for interactive acoustic renderings.

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Section: Plane Wave Expansion From Finite Element Datamentioning

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Low Frequency Interactive Auralization Based on a Plane Wave Expansion

2017

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“…To ensure that B is well-conditioned, we opt to regularize the problem by employing soft-limited radial filters, which have been shown to be nearly free of spatial and temporal artifacts [24], [25]. In this case it is possible to construct a regularized matrixB by substituting (21) into (18). With some notational changes, the modified radial functions are given as follows [24]:…”

Section: Numerical Formulationmentioning

confidence: 99%

“…[16], [17]. Of particular relevance here is a study by Southern et al [18], who suggested to spatially encode an FDTD sound field in ambisonics format using a differential receiver array and demonstrated loudspeaker-based auralizations for 2D grids using array orders up to 3. However, the literature on finite difference modeling still does not offer a broadband and robust method for directly rendering 3D binaural responses using free-field HRTFs.…”

Section: Introductionmentioning

confidence: 99%

Binaural Reproduction of Finite Difference Simulations Using Spherical Array Processing

Sheaffer

Walstijn

Rafaely

et al. 2015

IEEE/ACM Trans. Audio Speech Lang. Process.

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Abstract-Due to its efficiency and simplicity, the finite difference time domain method is becoming a popular choice for solving wideband, transient problems in various fields of acoustics. So far, the issue of extracting a binaural response from finite difference simulations has only been discussed in the context of embedding a listener geometry in the grid. In this paper we propose and study a method for binaural response rendering based on a spatial decomposition of the sound field. The finite difference grid is locally sampled using a volumetric array of receivers, from which a plane wave density function is computed and integrated with free-field head related transfer functions, in the spherical harmonics domain. The volumetric array is studied in terms of numerical robustness and spatial aliasing. Analytic formulas that predict the performance of the array are developed, facilitating spatial resolution analysis and numerical binaural response analysis for a number of finite difference schemes. Particular emphasis is placed on the effects of numerical dispersion on array processing and on the resulting binaural responses. Our method is compared to a binaural simulation based on the image method. Results indicate good spatial and temporal agreement between the two methods.

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“…For wave-based volumetric methods, previous approaches have followed from those used in spatial recording. Spherical array processing [15], [16] was employed for 3D ambisonic encoding in [17] and differential microphone processing [18], [19] was used in [20] to obtain 2D ambisonic signals. An alternative approach is through plane wave decomposition [21], [22].…”

Section: Introductionmentioning

confidence: 99%