28 research outputs found
Efficient Synthesis of Room Acoustics via Scattering Delay Networks
An acoustic reverberator consisting of a network of delay lines connected via
scattering junctions is proposed. All parameters of the reverberator are
derived from physical properties of the enclosure it simulates. It allows for
simulation of unequal and frequency-dependent wall absorption, as well as
directional sources and microphones. The reverberator renders the first-order
reflections exactly, while making progressively coarser approximations of
higher-order reflections. The rate of energy decay is close to that obtained
with the image method (IM) and consistent with the predictions of Sabine and
Eyring equations. The time evolution of the normalized echo density, which was
previously shown to be correlated with the perceived texture of reverberation,
is also close to that of IM. However, its computational complexity is one to
two orders of magnitude lower, comparable to the computational complexity of a
feedback delay network (FDN), and its memory requirements are negligible
Acoustic modeling using the digital waveguide mesh
The digital waveguide mesh has been an active area of music acoustics research for over ten years. Although founded in 1-D digital waveguide modeling, the principles on which it is based are not new to researchers grounded in numerical simulation, FDTD methods, electromagnetic simulation, etc. This article has attempted to provide a considerable review of how the DWM has been applied to acoustic modeling and sound synthesis problems, including new 2-D object synthesis and an overview of recent research activities in articulatory vocal tract modeling, RIR synthesis, and reverberation simulation. The extensive, although not by any means exhaustive, list of references indicates that though the DWM may have parallels in other disciplines, it still offers something new in the field of acoustic simulation and sound synth
The modeling of diffuse boundaries in the 2-D digital waveguide mesh
The digital waveguide mesh can be used to simulate the propagation of sound waves in an acoustic system. The accurate simulation of the acoustic characteristics of boundaries within such a system is an important part of the model. One significant property of an acoustic boundary is its diffusivity. Previous approaches to simulating diffuse boundaries in a digital waveguide mesh are effective but exhibit limitations and have not been analyzed in detail. An improved technique is presented here that simulates diffusion at boundaries and offers a high degree of control and consistency. This technique works by rotating wavefronts as they pass through a special diffusing layer adjacent to the boundary. The waves are rotated randomly according to a chosen probability function and the model is lossless. This diffusion model is analyzed in detail, and its diffusivity is quantified in the form of frequency dependent diffusion coefficients. The approach used to measuring boundary diffusion is described here in detail for the 2-D digital waveguide mesh and can readily be extended for the 3-D case
Equalities and Inequalities for Norms of Block Imaginary Circulant Operator Matrices
Circulant, block circulant-type matrices and operator norms have become effective tools in solving networked systems. In this paper, the block imaginary circulant operator matrices are discussed. By utilizing the special structure of such matrices, several norm equalities and inequalities are presented. The norm Ï„ in consideration is the weakly unitarily invariant norm, which satisfies Ï„A=Ï„(UAV). The usual operator norm and Schatten p-norm are included. Furthermore, some special cases and examples are given
Allpass Feedback Delay Networks
In the 1960s, Schroeder and Logan introduced delay line-based allpass
filters, which are still popular due to their computational efficiency and
versatile applicability in artificial reverberation, decorrelation, and
dispersive system design. In this work, we extend the theory of allpass systems
to any arbitrary connection of delay lines, namely feedback delay networks
(FDNs). We present a characterization of uniallpass FDNs, i.e., FDNs, which are
allpass for an arbitrary choice of delays. Further, we develop a solution to
the completion problem, i.e., given an FDN feedback matrix to determine the
remaining gain parameters such that the FDN is allpass. Particularly useful for
the completion problem are feedback matrices, which yield a homogeneous decay
of all system modes. Finally, we apply the uniallpass characterization to
previous FDN designs, namely, Schroeder's series allpass and Gardner's nested
allpass for single-input, single-output systems, and, Poletti's unitary
reverberator for multi-input, multi-output systems and demonstrate the
significant extension of the design space
Generalization of a 3-D resonator model for the simulation of spherical enclosures
A rectangular enclosure has such an even distribution of resonances that it
can be accurately and efficiently modelled using a feedback delay network.
Conversely, a non rectangular shape such as a sphere has a distribution of
resonances that challenges the construction of an efficient model. This work
proposes an extension of the already known feedback delay network structure to
model the resonant properties of a sphere. A specific frequency distribution of
resonances can be approximated, up to a certain frequency, by inserting an
allpass filter of moderate order after each delay line of a feedback delay
network. The structure used for rectangular boxes is therefore augmented with a
set of allpass filters allowing parametric control over the enclosure size and
the boundary properties. This work was motivated by informal listening tests
which have shown that it is possible to identify a basic shape just from the
distribution of its audible resonances.Comment: 39 pages, 16 figures, 6 tables. Accepted for publication in Applied
Signal Processin
Modal Decomposition of Feedback Delay Networks
Feedback delay networks (FDNs) belong to a general class of recursive filters
which are widely used in sound synthesis and physical modeling applications. We
present a numerical technique to compute the modal decomposition of the FDN
transfer function. The proposed pole finding algorithm is based on the
Ehrlich-Aberth iteration for matrix polynomials and has improved computational
performance of up to three orders of magnitude compared to a scalar polynomial
root finder. We demonstrate how explicit knowledge of the FDN's modal behavior
facilitates analysis and improvements for artificial reverberation. The
statistical distribution of mode frequency and residue magnitudes demonstrate
that relatively few modes contribute a large portion of impulse response
energy
Scattering Delay Network Simulator of Coupled Volume Acoustics
IEEEArtificial reverberators provide a computationally viable alternative to full-scale room acoustics simulation methods for deployment in interactive, immersive systems. Scattering delay network (SDN) is an artificial reverberator that allows direct parametric control over the geometry of a simulated cuboid enclosure as well as the directional characteristics of the simulated sound sources and microphones. This paper extends the concept of SDN reverberators to multiple enclosures coupled via an aperture. The extension allows independent control of the acoustical properties of the coupled enclosures and the size of the connecting aperture. The transfer function of the coupled-volume SDN system is derived. The effectiveness of the proposed method is evaluated in terms of rendered energy decay curves in comparison to full-scale ray-tracing models and scale model measurements
Differentiable Artificial Reverberation
Artificial reverberation (AR) models play a central role in various audio
applications. Therefore, estimating the AR model parameters (ARPs) of a target
reverberation is a crucial task. Although a few recent deep-learning-based
approaches have shown promising performance, their non-end-to-end training
scheme prevents them from fully exploiting the potential of deep neural
networks. This motivates to introduce differentiable artificial reverberation
(DAR) models which allows loss gradients to be back-propagated end-to-end.
However, implementing the AR models with their difference equations "as is" in
the deep-learning framework severely bottlenecks the training speed when
executed with a parallel processor like GPU due to their infinite impulse
response (IIR) components. We tackle this problem by replacing the IIR filters
with finite impulse response (FIR) approximations with the frequency-sampling
method (FSM). Using the FSM, we implement three DAR models -- differentiable
Filtered Velvet Noise (FVN), Advanced Filtered Velvet Noise (AFVN), and
Feedback Delay Network (FDN). For each AR model, we train its ARP estimation
networks for analysis-synthesis (RIR-to-ARP) and blind estimation
(reverberant-speech-to-ARP) task in an end-to-end manner with its DAR model
counterpart. Experiment results show that the proposed method achieves
consistent performance improvement over the non-end-to-end approaches in both
objective metrics and subjective listening test results.Comment: Manuscript submitted to TASL
Meta-Programming and Policy-Based Design as a Technique of Architecting Modular and Efficient DSP Algorithm Implementations
Meta-programming paradigm and policy-based design are less known programming techniques in Digital Signal Processing (DSP) community, used to coding in pure C or assembly language. Major software components, like C++ STL, have proven usefulness of such paradigms in providing top performance of highly optimised native code, along with abstraction and modularity necessary in complex software projects. This paper describes composition of DSP code using these techniques, bringing as an example implementation of Feedback Delay Network (FDN) artificial reverberation algorithm. The proposed approach was proven to be practical, especially in case of prototyping computationally intense algorithms. To provide further performance insight, we discuss the techniques in context of other optimisation methods, like Single Instruction Multiple Data (SIMD) instruction sets usage and exploitation of superscalar architecture capabilities