Paper Archive

Live music performances and music production often involve the manipulation of several parameters during sound generation, processing, and mixing. In hardware layouts, those parameters are usually controlled using knobs, sliders and buttons. When these layouts are virtualized, the use of physical (e.g. MIDI) controllers can make interaction easier and reduce the cognitive load associated to sound manipulation. The addition of haptic feedback can further improve such interaction by facilitating the detection of the nature (continuous / discrete) and value of a parameter. To this end, we have realized an endless-knob controller prototype with programmable resistance to rotation, able to render various haptic effects. Ten subjects assessed the effectiveness of the provided haptic feedback in a target-matching task where either visual-only or visual-haptic feedback was provided; the experiment reported significantly lower errors in presence of haptic feedback. Finally, the knob was configured as a multi-parametric controller for a real-time audio effect software written in Python, simulating the voltage-controlled filter aboard the EMS VCS3. The integration of the sound algorithm and the haptic knob is discussed, together with various haptic feedback effects in response to control actions.

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Measuring the auditory lateralization elicited by interaural time difference (ITD) cues involves the estimation of a psychometric function (PF). The shape of this function usually follows from the analysis of the subjective data and models the probability of correctly localizing the angular position of a sound source. The present study describes and evaluates a procedure for progressively fitting a PF, using Gaussian process classification of the subjective responses produced during a binary decision experiment. The process refines adaptively an approximated PF, following Bayesian inference. At each trial, it suggests the most informative auditory stimulus for function refinement according to Bayesian active learning by disagreement (BALD) mutual information. In this paper, the procedure was modified to accommodate two-alternative forced choice (2AFC) experimental methods and then was compared with a standard adaptive “three-down, one-up” staircase procedure. Our process approximates the average threshold ITD 79.4% correct level of lateralization with a mean accuracy increase of 8.9% over the Weibull function fitted on the data of the same test. The final accuracy for the Just Noticeable Difference (JND) in ITD is achieved with only 37.6% of the trials needed by a standard lateralization test.

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The development of audio Digital Signal Processing (DSP) algorithms typically requires iterative design, analysis, and testing, possibly on different target platforms, furthermore often asking for resets or restarts of execution environments between iterations. Manually performing deployment, setup, and output data collection can quickly become intolerably time-consuming. Therefore, we propose a new, experimental, open-ended, and automatable protocol to separate the coding, building, and deployment tasks onto different network nodes. The proposed protocol is mostly based on widespread technology and designed to be easy to implement and integrate with existing software infrastructure. Its flexibility has been validated through a proof-of-concept implementation. Despite being still in its infancy, it already shows potential in allowing faster and more comfortable development workflows.

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For their low and constant computational cost, non-iterative methods for the solution of differential problems are gaining popularity in virtual analog provided their stability properties and accuracy level afford their use at no exaggerate temporal oversampling. At least in some application case studies, one recent family of noniterative schemes has shown promise to outperform methods that achieve accurate results at the cost of iterating several times while converging to the numerical solution. Here, this family is contextualized and studied against known classes of non-iterative methods. The results from these studies foster a more general discussion about the possibilities, role and prospective use of non-iterative methods in virtual analog.

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