Download An Extension for Source Separation Techniques Avoiding Beats The problem of separating individual sound sources from a mixture of these, known as Source Separation or Computational Auditory Scene Analysis (CASA), has become popular in the recent decades. A number of methods have emerged from the study of this problem, some of which perform very well for certain types of audio sources, e.g. speech. For separation of instruments in music, there are several shortcomings. In general when instruments play together they are not independent of each other. More specifically the time-frequency distributions of the different sources will overlap. Harmonic instruments in particular have high probability of overlapping partials. If these overlapping partials are not separated properly, the separated signals will have a different sensation of roughness, and the separation quality degrades. In this paper we present a method to separate overlapping partials in stereo signals. This method looks at the shapes of partial envelopes, and uses minimization of the difference between such shapes in order to demix overlapping partials. The method can be applied to enhance existing methods for source separation, e.g. blind source separation techniques, model based techniques, and spatial separation techniques. We also discuss other simpler methods that can work with mono signals.
Download Real Time Modeling of Acoustic Propagation in Complex Environments In order to achieve high-quality audio-realistic rendering in complex environments, we need to determine all the acoustic paths that go from sources to receivers, due to specular reflections as well as diffraction phenomena. In this paper we propose a novel method for computing and auralizing the reflected as well as the diffracted field in 2.5D environments. The method is based on a preliminary geometric analysis of the mutual visibility of the environment reflectors. This allows us to compute on the fly all possible acoustic paths, as the information on sources and receivers becomes available. The construction of a beam tree, in fact, is here performed through a look-up of visibility information and the determination of acoustic paths is based on a lookup on the computed beam tree. We also show how to model diffraction using the same beam tree structure used for modeling reflection and transmission. In order to validate the method we conducted an acquisition campaign over a real environment and compared the results obtained with our real-time simulation system.
Download Extended Source-Filter Model for Harmonic Instruments for Expressive Control of Sound Synthesis and Transformation In this paper we present a revised and improved version of a recently proposed extended source-filter model for sound synthesis, transformation and hybridization of harmonic instruments. This extension focuses mainly on the application for impulsively excited instruments like piano or guitar, but also improves synthesis results for continuously driven instruments including their hybrids. This technique comprises an extensive analysis of an instruments sound database, followed by the estimation of a generalized instrument model reflecting timbre variations according to selected control parameters. Such an instrument model allows for natural sounding transformations and expressive control of instrument sounds regarding its control parameters.
Download Modelling of nonlinear state-space systems using a deep neural network In this paper we present a new method for the pseudo black-box modelling of general continuous-time state-space systems using a discrete-time state-space system with an embedded deep neural network. Examples are given of how this method can be applied to a number of common nonlinear electronic circuits used in music technology, namely two kinds of diode-based guitar distortion circuits and the lowpass filter of the Korg MS-20 synthesizer.
Download SCAPES: Semantically Conditioned Autoregressive Prior for Environmental Sounds This paper presents SCAPES, a semantically conditioned autoregressive prior for environmental sound generation. The system models discrete audio representations using an autoregressive architecture conditioned on semantic information, enabling the generation of environmental sounds that follow user-specified concepts. By learning a prior over audio tokens, SCAPES combines high-level semantic control with detailed temporal modeling. Experimental evaluation investigates the quality, diversity, and semantic consistency of generated sounds, demonstrating the potential of autoregressive priors for controllable environmental sound synthesis.
Download Explicit Wave Digital Model of the Fulltone OCD Pedal Based on Canonical Piecewise-Linear Functions Virtual Analog (VA) modeling aims at digitally emulating analog audio equipment while preserving its characteristic nonlinear behavior and musical expressiveness. In the context of guitar effects, overdrive pedals represent a cornerstone of many signal chains, as they strongly contribute to the perceived dynamics, articulation, and timbral identity of the instrument. Among these, the Fulltone OCD overdrive is considered a standard in both studio and live environments, being widely adopted across rock and metal genres. In this article, we present an explicit Wave Digital (WD) model of the Fulltone OCD (v2) pedal. By exploiting the circuit topology, the MOSFETs and the germanium diode composing the asymmetric clipping stage are grouped into a single equivalent nonlinear element, enabling an explicit WD realization that avoids costly iterative solvers. The resulting nonlinear characteristic is approximated by means of a Canonical Piecewise-Linear (CPWL) function, yielding a compact and efficient explicit model suitable for real-time implementation. The proposed model is validated against reference simulations and implemented both in MATLAB and as a real-time audio plug-in using the JUCE framework.
Download An Efficient Pitch-Tracking Algorithm Using A Combination Of Fourier Transforms In this paper we present a technique for detecting the pitch of sound using a series of two forward Fourier transforms. We use an enhanced version of the Fourier transform for a better accuracy, as well as a tracking strategy among pitch candidates for an increased robustness. This efficient technique allows us to precisely find out the pitches of harmonic sounds such as the voice or classic musical instruments, but also of more complex sounds like rippled noises.
Download Audio Signal Extrapolation - Theory and Applications A method for extrapolating discrete audio signals is described. The theory of extrapolation is studied and some applications are presented and demonstrated. The extrapolation method is fast and capable of extrapolating several thousand samples of CD-quality audio signals. The extrapolation is applied in practice to enhance the spectral resolution in short-time fast Fourier transform based methods. It is also applied to eliminate impulsive noise bursts and to recover missing signal sections.
Download Real-Time Wave Digital Simulation of Cascaded Vacuum Tube Amplifiers using Modified Blockwise Method Vacuum tube amplifiers, known for their acclaimed distortion characteristics, are still widely used in hi-fi audio devices. However, bulky, fragile and power-consuming vacuum tube devices have also motivated much research on digital emulation of vacuum tube amplifier behaviors. Recent studies on Wave Digital Filters (WDF) have made possible the modeling of multi-stage vacuum tube amplifiers within single WDF SPQR trees. Our research combines the latest progress on WDF with the modified blockwise method to reduce the overall computational complexity of modeling cascaded vacuum tube amplifiers by decomposing the whole circuit into several small stages containing only two adjacent triodes. Certain performance optimization methods are discussed and applied in the eventual real-time implementation.
Download Antiderivative Antialiasing in Nonlinear Wave Digital Filters 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.