Download Barberpole Phasing and Flanging Illusions Various ways to implement infinitely rising or falling spectral notches, also known as the barberpole phaser and flanging illusions, are described and studied. The first method is inspired by the Shepard-Risset illusion, and is based on a series of several cascaded notch filters moving in frequency one octave apart from each other. The second method, called a synchronized dual flanger, realizes the desired effect in an innovative and economic way using two cascaded time-varying comb filters and cross-fading between them. The third method is based on the use of single-sideband modulation, also known as frequency shifting. The proposed techniques effectively reproduce the illusion of endlessly moving spectral notches, particularly at slow modulation speeds and for input signals with a rich frequency spectrum. These effects can be programmed in real time and implemented as part of a digital audio processing system.
Download Modulation Extraction for LFO-driven Audio Effects Low frequency oscillator (LFO) driven audio effects such as phaser, flanger, and chorus, modify an input signal using time-varying filters and delays, resulting in characteristic sweeping or widening effects. It has been shown that these effects can be modeled using neural networks when conditioned with the ground truth LFO signal. However, in most cases, the LFO signal is not accessible and measurement from the audio signal is nontrivial, hindering the modeling process. To address this, we propose a framework capable of extracting arbitrary LFO signals from processed audio across multiple digital audio effects, parameter settings, and instrument configurations. Since our system imposes no restrictions on the LFO signal shape, we demonstrate its ability to extract quasiperiodic, combined, and distorted modulation signals that are relevant to effect modeling. Furthermore, we show how coupling the extraction model with a simple processing network enables training of end-to-end black-box models of unseen analog or digital LFO-driven audio effects using only dry and wet audio pairs, overcoming the need to access the audio effect or internal LFO signal. We make our code available and provide the trained audio effect models in a real-time VST plugin1 .
Download Explicit Vector Wave Digital Filter Modeling of Circuits with a Single Bipolar Junction Transistor The recently developed extension of Wave Digital Filters based on vector wave variables has broadened the class of circuits with linear two-port elements that can be modeled in a modular and explicit fashion in the Wave Digital (WD) domain. In this paper, we apply the vector definition of wave variables to nonlinear twoport elements. In particular, we present two vector WD models of a Bipolar Junction Transistor (BJT) using characteristic equations derived from an extended Ebers-Moll model. One, implicit, is based on a modified Newton-Raphson method; the other, explicit, is based on a neural network trained in the WD domain and it is shown to allow fully explicit implementation of circuits with a single BJT, which can be executed in real time.
Download DDSP-Based Neural Waveform Synthesis of Polyphonic Guitar Performance From String-Wise MIDI Input We explore the use of neural synthesis for acoustic guitar from string-wise MIDI input. We propose four different systems and compare them with both objective metrics and subjective evaluation against natural audio and a sample-based baseline. We iteratively develop these four systems by making various considerations on the architecture and intermediate tasks, such as predicting pitch and loudness control features. We find that formulating the control feature prediction task as a classification task rather than a regression task yields better results. Furthermore, we find that our simplest proposed system, which directly predicts synthesis parameters from MIDI input performs the best out of the four proposed systems. Audio examples and code are available.
Download Characterisation and Excursion Modelling of Audio Haptic Transducers Statement and calculation of objective audio haptic transducer performance metrics facilitates optimisation of multi-sensory sound reproduction systems. Measurements of existing haptic transducers are applied to the calculation of a series of performance metrics to demonstrate a means of comparative objective analysis. The frequency response, transient response and moving mass excursion characteristics of each measured transducer are quantified using novel and previously defined metrics. Objective data drawn from a series of practical measurements shows that the proposed metrics and means of excursion modelling applied herein are appropriate for haptic transducer evaluation and protection against over-excursion respectively.
Download Modeling and Extending the Rca Mark Ii Sound Effects Filter We have analyzed the Sound Effects Filter from the one-of-a-kind RCA Mark II sound synthesizer and modeled it as a Wave Digital Filter using the Faust language, to make this once exclusive device widely available. By studying the original schematics and measurements of the device, we discovered several circuit modifications. Building on these, we proposed a number of extensions to the circuit which increase its usefulness in music production.
Download FDNTB: The Feedback Delay Network Toolbox Feedback delay networks (FDNs) are recursive filters, which are
widely used for artificial reverberation and decorrelation. While
there exists a vast literature on a wide variety of reverb topologies,
this work aims to provide a unifying framework to design and analyze delay-based reverberators. To this end, we present the Feedback Delay Network Toolbox (FDNTB), a collection of the MATLAB functions and example scripts. The FDNTB includes various representations of FDNs and corresponding translation functions. Further, it provides a selection of special feedback matrices,
topologies, and attenuation filters. In particular, more advanced
algorithms such as modal decomposition, time-varying matrices,
and filter feedback matrices are readily accessible. Furthermore,
our toolbox contains several additional FDN designs. Providing
MATLAB code under a GNU-GPL 3.0 license and including illustrative examples, we aim to foster research and education in the
field of audio processing.
Download A Virtual Instrument for Ifft-Based Additive Synthesis in the Ambisonics Domain Spatial additive synthesis can be efficiently implemented by applying the inverse Fourier transform to create the individual channels of Ambisonics signals. In the presented work, this approach has been implemented as an audio plugin, allowing the generation and control of basic waveforms and their spatial attributes in a typical DAW-based music production context. Triggered envelopes and low frequency oscillators can be mapped to the spectral shape, source position and source width of the resulting sounds. A technical evaluation shows the computational advantages of the proposed method for additive sounds with high numbers of partials and different Ambisonics orders. The results of a user study indicate the potential of the developed plugin for manipulating the perceived position, source width and timbre coloration.
Download Evaluating AI Coding Assistants in Audio DSP Education: A Small Scale Study Recent advances in AI-assisted coding tools raise questions about how programming-intensive subjects such as audio digital signal processing should be taught and how exam projects should be evaluated. This paper presents a small-scale controlled exploratory study conducted in a graduate course on music DSP. As a final project at the end of the course, the students implemented a modular synthesizer plugin in C++. Half of the students had access to AI-assisted coding support, while the other group developed the plugin manually. All students had to follow a protocol and provide data at the end of the project, together with their code, which was discussed with them as part of the course exam. Although the scale of the study is small, the paper shares a qualitative analysis of the results and a few takeaway messages for future reference among lecturers in the field. Overall, AI-assisted coding does provide some advantage to students but only in certain regards. The used AI tools, trained on GitHub repositories, seem to have only partial awareness of the state of the art in digital audio processing (e.g. antialiasing oscillators, virtual analog filters, etc.). Finally, the use of AI seems to not interfere excessively with the ability of the students to learn from their practical experience.
Download Improving Elevation Perception with a Tool for Image-guided Head-related Transfer Function Selection This paper proposes an image-guided HRTF selection procedure that exploits the relation between features of the pinna shape and HRTF notches. Using a 2D image of a subject’s pinna, the procedure selects from a database the HRTF set that best fits the anthropometry of that subject. The proposed procedure is designed to be quickly applied and easy to use for a user without previous knowledge on binaural audio technologies. The entire process is evaluated by means of an auditory model for sound localization in the mid-sagittal plane available from previous literature. Using virtual subjects from a HRTF database, a virtual experiment is implemented to assess the vertical localization performance of the database subjects when they are provided with HRTF sets selected by the proposed procedure. Results report a statistically significant improvement in predictions of localization performance for selected HRTFs compared to KEMAR HRTF which is a commercial standard in many binaural audio solutions; moreover, the proposed analysis provides useful indications to refine the perceptually-motivated metrics that guides the selection.