Matteo Scerbo’s research while affiliated with University of Surrey and other places

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Publications (7)


MoD-ART: Modal Decomposition of Acoustic Radiance Transfer
  • Preprint

December 2024

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27 Reads

Matteo Scerbo

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[...]

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Enzo De Sena

Modeling late reverberation at interactive speeds is a challenging task when multiple sound sources and listeners are present in the same environment. This is especially problematic when the environment is geometrically complex and/or features uneven energy absorption (e.g. coupled volumes), because in such cases the late reverberation is dependent on the sound sources' and listeners' positions, and therefore must be adapted to their movements in real time. We present a novel approach to the task, named modal decomposition of Acoustic Radiance Transfer (MoD-ART), which can handle highly complex scenarios with efficiency. The approach is based on the geometrical acoustics method of Acoustic Radiance Transfer, from which we extract a set of energy decay modes and their positional relationships with sources and listeners. In this paper, we describe the physical and mathematical meaningfulness of MoD-ART, highlighting its advantages and applicability to different scenarios. Through an analysis of the method's computational complexity, we show that it compares very favourably with ray-tracing. We also present simulation results showing that MoD-ART can capture multiple decay slopes and flutter echoes.


Fig. 1: Modal shapes of an FDN with N " 3 delay lines are depicted. The solid black curves represent the real part of a low-frequency right eigenvector along the delay line. The dashed grey curves are the corresponding left eigenvectors. Varying the positions of the input and output taps along the delay lines implements the proposed modal excitation control.
Fig. 2: State-space formulation of the FDN in Fig. 1 according to (3). In the state-space representation, the delay states are depicted from output to input, running top to bottom.
Fig. 3: Real part of the right Eigenvector of the example FDN. (Top) The state space has N " 55 entries (rows) and the same number of eigenvectors (columns), but only half of them are shown as the rest are complex conjugates. The Eigenvectors are sorted from low to high frequency. The states of the three delay lines are separated by thick black lines, which indicate the delay-line outputs. (Bottom) Delay statespace Eigenvectors v are the delay-line outputs of v .
Fig. 4: Spectrogram of a pulse train with varying intap position on the third delay line going from start to end. The difference in modal excitation follows the modal shape in Fig. 1.
Modal Excitation in Feedback Delay Networks
  • Preprint
  • File available

March 2024

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162 Reads

Feedback delay networks (FDNs) are used in audio processing and synthesis. The modal shapes of the system describe the modal excitation by input and output signals. Previously, the Ehrlich-Aberth method was used to find modes in large FDNs. Here, the method is extended to the corresponding eigenvectors indicating the modal shape. In particular, the computational complexity of the proposed analysis method does not depend on the delay-line lengths and is thus suitable for large FDNs, such as artificial reverberators. We show the relation between the compact generalized eigenvectors in the delay state space and the spatially extended modal shapes in the state space. We illustrate this method with an example FDN in which the suggested modal excitation control does not increase the computational cost. The modal shapes can help optimize input and output gains. This letter teaches how selecting the input and output points along the delay lines of an FDN adjusts the spectral shape of the system output.

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Room Acoustic Rendering Networks With Control of Scattering and Early Reflections

January 2024

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25 Reads

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2 Citations

IEEE/ACM Transactions on Audio Speech and Language Processing

Room acoustic synthesis can be used in virtual reality (VR), augmented reality (AR) and gaming applications to enhance listeners' sense of immersion, realism and externalisation. A common approach is to use geometrical acoustics (GA) models to compute impulse responses at interactive speed, and fast convolution methods to apply said responses in real time. Alternatively, delay-network-based models are capable of modeling certain aspects of room acoustics, but with a significantly lower computational cost. In order to bridge the gap between these classes of models, recent work introduced delay network designs that approximate Acoustic Radiance Transfer (ART), a GA model that simulates the transfer of acoustic energy between discrete surface patches in an environment. This paper presents two key extensions of such designs. The first extension involves a new physically-based and stability-preserving design of the feedback matrices, enabling more accurate control of scattering and, more in general, of late reverberation properties. The second extension allows an arbitrary number of early reflections to be modeled with high accuracy, meaning the network can be scaled at will between computational cost and early reverberation precision. The proposed extensions are compared to the baseline ART approximating delay network as well as two reference GA models. The evaluation is based on objective measures of perceptually relevant features, including frequency-dependent reverberation times, echo density build-up, and early decay time. Results show how the proposed extensions result in a significant improvement over the baseline model, especially for the case of non-convex geometries or the case of unevenly distributed wall absorption, both scenarios of broad practical interest


Fig. 1: Modal shapes of an FDN with N " 3 delay lines are depicted. The solid gray curves represent the real part of a low-frequency continuous right eigenvector along the delay line while the black dots represent the sampled delay units. Varying the positions of the input and output taps along the delay lines implements the proposed modal excitation control.
Fig. 2: State-space formulation of the FDN in Fig. 1 according to (3). In the state-space representation, the delay states are depicted from output to input, running top to bottom.
Fig. 3: Real part of the right eigenvector of the example FDN. (Top) The state space has N " 55 entries (rows) and the same number of eigenvectors (columns), but only half of them are shown as the rest are complex conjugates. The eigenvectors are sorted from low to high frequency. The states of the three delay lines are separated by thick black lines, which indicate the delay-line outputs. (Bottom) Delay state-space eigenvectors v are the delay-line outputs of v .
Fig. 4: Spectrogram of a pulse train with varying intap position on the third delay line going from start to end corresponding to state space indices 33-55. The difference in modal excitation follows the modal shape in Fig. 3.
Modal Excitation in Feedback Delay Networks

January 2024

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46 Reads

Signal Processing Letters, IEEE

Feedback delay networks (FDNs) are used in audio processing and synthesis. The modal shapes of the system describe the modal excitation by input and output signals. Previously, the Ehrlich-Aberth method was used to find modes in large FDNs. Here, the method is extended to the corresponding eigenvectors indicating the modal shape. In particular, the computational complexity of the proposed analysis method does not depend on the delay-line lengths and is thus suitable for large FDNs, such as artificial reverberators. We show the relation between the compact generalized eigenvectors in the delay state space and the spatially extended modal shapes in the state space. We illustrate this method with an example FDN in which the suggested modal excitation control does not increase the computational cost. The modal shapes can help optimize input and output gains. This letter teaches how selecting the input and output points along the delay lines of an FDN adjusts the spectral shape of the system output.



Parameters used for the room simulations.
T60 values achieved by the compared methods.
Mean values and standard deviations for the naturalness ratings of the compared methods. Means report the 95% confi- dence interval.
Results of Mann-Whitney tests for several pairs of meth- ods. The number of samples is 108 for all cases, meaning the Mann-Whitney U statistic should be interpreted as U (108, 108). z is its standardized value.
Higher-order Scattering Delay Networks for Artificial Reverberation

September 2022

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83 Reads

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3 Citations

Computer simulations of room acoustics suffer from an efficiency vs accuracy trade-off, with highly accurate wave-based models being highly computationally expensive, and delay-network-based models lacking in physical accuracy. The Scattering Delay Network (SDN) is a highly efficient recursive structure that renders first order reflections exactly while approximating higher order ones. With the purpose of improving the accuracy of SDNs, in this paper, several variations on SDNs are investigated, including appropriate node placement for exact modeling of higher order reflections , redesigned scattering matrices for physically-motivated scattering, and pruned network connections for reduced computational complexity. The results of these variations are compared to state-of-the-art geometric acoustic models for different shoebox room simulations. Objective measures (Normalized Echo Densities (NEDs) and Energy Decay Curves (EDCs)) showed a close match between the proposed methods and the references. A formal listening test was carried out to evaluate differences in perceived naturalness of the synthesized Room Impulse Responses. Results show that increasing SDNs' order and adding directional scattering in a fully-connected network improves perceived naturalness, and higher-order pruned networks give similar performance at a much lower computational cost.


Citations (4)


... Potter, Cvetković, and De Sena (2022) found that adding room acoustic rendering to head-tracked binaural audio enhances audience immersion to the same extent as increasing video resolution fivefold. This modeling approach mainly involves predicting and reproducing some of the most important characteristics of room acoustics, explaining acoustic phenomena based on the physical laws of sound wave propagation (Scerbo, Savioja, & De Sena, 2024). The positive audience response to sound suggests a strong correlation between the content and quality of sound and audience immersion. ...

Reference:

Should teaching strategies emphasize emotion or competence? Enhancing audience acceptance of children with autism through online music performances -evidence from China
Room Acoustic Rendering Networks With Control of Scattering and Early Reflections
  • Citing Article
  • January 2024

IEEE/ACM Transactions on Audio Speech and Language Processing

... Data-driven models incorporating a physical prior based on the boundary integral equation (BIE) [32] include the equivalent source model (ESM) [33][34][35] and the boundary integral operator state-space (BIOSS) model [36]. Even though the BIE is a wave-based prior, it asymptotically admits a geometric solution [37], hence these models are capable of representing both wave-based and geometric sound behavior. Purely physical models have mainly been used in virtual acoustics and include reflection path models [38] (e.g., image source models (ISM) [39], ray tracing (RT) [40], and beam tracing (BT) [41]), delay networks (e.g., feedback delay networks (FDN) [42], digital waveguide networks (DWN) [43], and scattering delay networks (SDN) [44]), and discretized partial differential equation (PDE) models (e.g., boundary element (BEM) [45], finite element (FEM) [46], finite difference (FDM) [9,47], and finite volume models (FVM) [8]). ...

Relating wave-based and geometric acoustics using a stationary phase approximation approximation of the boundary integral equation
  • Citing Conference Paper
  • January 2022

... The scattering delay network (SDN) is an artificial reverberator originally proposed by De Sena et al. [12] and later refined [13,14] and extended [23][24][25][26]. The authors' goal was to provide an efficient, interactive, and scalable synthesis of room reverberation for video games, while providing explicit control over physical properties of the room. ...

Low-Complexity Higher Order Scattering Delay Networks
  • Citing Conference Paper
  • October 2023

... The scattering delay network (SDN) is an artificial reverberator originally proposed by De Sena et al. [12] and later refined [13,14] and extended [23][24][25][26]. The authors' goal was to provide an efficient, interactive, and scalable synthesis of room reverberation for video games, while providing explicit control over physical properties of the room. ...

Higher-order Scattering Delay Networks for Artificial Reverberation