Paper Archive

There are several algorithms and approaches to Room Impulse Response (RIR) estimation. To the best of the author’s knowledge, there is no documentation of accuracy, speed, or even the feasibility of using signed distance functions (SDFs) in combination with sphere tracing for this task. A proof of concept with a focus on real-time performance is presented here, which still lacks many features such as frequency-dependent absorption and scattering coefficients, arbitrary source and receiver directives etc. The results are then compared to real room impulse responses and to a different simulation algorithm. Also, the rather special merits of such an approach, such as 4D reverberation and simple rounding of geometry, are briefly discussed and presented.

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Virtual reality applications require all kinds of methods to create plausible virtual acoustics environments to enhance the user experience. Here, we present an acoustic paintbrush method that modifies the timbre of a simple room acoustics simulation with the timbre of a measured room response while aiming to preserve the spatial aspects of the simulated room. In other words, the method only applies the measured spectral coloration and alters the simulated and temporal distribution of early reflections as little as possible. Three variations of the acoustic paintbrush method are validated with a listening test. The results indicate that the method works reasonably well. The paintbrushed room acoustic simulations were perceived to become closer to the measured room acoustics than the source simulation. However, the limits of the perceived effect varied depending on the input signal and the simulated and recorded responses. This warrants for further perceptual testing.

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Reverberation is one of the most important effects used in audio production. Although nowadays numerous real-time implementations of artificial reverberation algorithms are available, many of them depend on a database of recorded or pre-synthesized room impulse responses, which are convolved with the input signal. Implementations that use an algorithmic approach are more flexible but do not let the users have full control over the produced sound, allowing only a few selected parameters to be altered. The realtime implementation of an artificial reverberation synthesizer presented in this study introduces an audio plugin based on a feedback delay network (FDN), which lets the user have full and detailed insight into the produced reverb. It allows for control of reverberation time in ten octave bands, simultaneously allowing adjusting the feedback matrix type and delay-line lengths. The proposed plugin explores various FDN setups, showing that the lowest useful order for high-quality sound is 16, and that in the case of a Householder matrix the implementation strongly affects the resulting reverberation. Experimenting with delay lengths and distribution demonstrates that choosing too wide or too narrow a length range is disadvantageous to the synthesized sound quality. The study also discusses CPU usage for different FDN orders and plugin states.

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Reverb provides psychoacoustic cues that convey information concerning relative locations within an acoustical space. The need arises often in audio production to impart an acoustic context on an audio track that resembles a reference track. One tool for making audio tracks appear to be recorded in the same space is by applying reverb to a dry track that is similar to the reverb in a wet one. This paper presents a model for the task of “reverb matching,” where we attempt to automatically add artificial reverb to a track, making it sound like it was recorded in the same space as a reference track. We propose a model architecture for performing reverb matching and provide subjective experimental results suggesting that the reverb matching model can perform as well as a human. We also provide open source software for generating training data using an arbitrary Virtual Studio Technology plug-in.

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Various audio signal processing applications, such as source separation and dereverberation, require an accurate mathematical modeling of the input audio data. In the literature, many works have focused on source signal modeling, while the reverberation model is often kept very simplistic. This paper aims to investigate a stochastic room impulse response model presented in a previous article: this model is first adapted to discrete time, then we propose a parametric estimation algorithm, that we evaluate experimentally. Our results show that this algorithm is able to efficiently estimate the model parameters, in various experimental settings (various signal-to-noise ratios and absorption coefficients of the room walls).

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In the design of real-time spring reverberation algorithms, a modal architecture offers several advantages, including computational efficiency and parametric control flexibility. Due to the complex, highly dispersive behavior of helical springs, computing physically accurate parameters for such a model presents specific challenges. In this paper these are addressed by applying an implicit higher-order-in-space finite difference scheme to a two-variable model of helical spring dynamics. A novel numerical boundary treatment is presented, which utilises multiple centered boundary expressions of different stencil width. The resulting scheme is unconditionally stable, and as such allows adjusting the numerical parameters independently of each other and of the physical parameters. The dispersion relation of the scheme is shown to be accurate in the audio range only for very high orders of accuracy in combination with a small temporal and spatial step. The frequency, amplitude, and decay rate of the system modes are extracted from a diagonalised form of this numerical model. After removing all modes with frequencies outside the audio range and applying a modal amplitude correction to compensate for omitting the magnetic transducers, a light-weight modal reverb algorithm is obtained. Comparison with a measured impulse response shows a reasonably good match across a wide frequency range in terms of echo density, decay characteristics, and diffusive nature.

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A novel algorithm for fast convolution reverberation is proposed. The convolution is implemented as partitioned convolution in the frequency domain. We show that computational cost can be reduced when multiplying the spectra of the impulse response with the spectra of the input signal by using only a fraction of the bins of the original spectra and by discarding phase information. Reordering the bins of the spectra allows to avoid overhead incurred by randomly accessing bins in the spectrum. The proposed algorithm is considerably faster than conventional partitioned convolution and perceptual convolution, where bins with low amplitudes are discarded. Speed increases depend on the impulse response used. For an impulse response of around 3 s length at 48 kHz sampling rate execution took only about 40 % of the time necessary for conventional partitioned convolution and 61 % of the time needed for perceptual convolution. A listening test showed that there is only a very slight degradation in quality, which can probably be neglected for implementations where speed is crucial. Sound samples are provided.

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The Red Llama guitar overdrive effect pedal differs from most other overdrive effects because it utilizes CMOS inverters, formed by two metal-oxide-semiconductor field-effect transistors (MOSFETs), instead of a combination of operational amplifiers and diodes to obtain nonlinear distortion. This makes it an interesting subject for virtual analog modeling, obviously requiring a suitable model for the CMOS inverters. Therefore, in this paper, we extend a well-known model for MOSFETs by a straight-forward heuristic approach to achieve a good match between the model and measurement data obtained for the individual MOSFETs. This allows a faithful digital simulation of the Red Llama.

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A major problem in the emulation of discrete-time nonlinear systems, such as those encountered in Virtual Analog modeling, is aliasing distortion. A trivial approach to reduce aliasing is oversampling. However, this solution may be too computationally demanding for real-time applications. More advanced techniques to suppress aliased components are arbitrary-order Antiderivative Antialiasing (ADAA) methods that approximate the reference nonlinear function using a combination of its antiderivatives of different orders. While in its original formulation it is applied only to memoryless systems, recently, the applicability of first-order ADAA has been extended to stateful systems employing their statespace description. This paper presents an alternative formulation that successfully applies arbitrary-order ADAA methods to Wave Digital Filter models of dynamic circuits with one nonlinear element. It is shown that the proposed approach allows us to design ADAA models of the nonlinear elements in a fully local and modular fashion, independently of the considered reference circuit. Further peculiar features of the proposed approach, along with two examples of applications, are discussed.

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We propose a new style of continuous-time filter design composed of a cascade of 2nd-order state variable filters (SVFs) and a global feedback path. This family of filters is parameterized by the SVF cutoff frequencies and resonances, as well as the global feedback amount. For the case of two identical SVFs in cascade and a specific value of the SVF resonance, the proposed design reduces to the well-known Moog ladder filter. For another resonance value, it approximates the Octave CAT filter. The resonance parameter can be used to create new filters as well. We study the pole loci and transfer functions of the SVF building block and entire filter. We focus in particular on the effect of the proposed parameterization on important aspects of the filter’s response, including the passband gain and cutoff frequency error. We also present the first in-depth study of the Octave CAT filter circuit.

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