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Session 1: Virtual Analog: JUDY NAJNUDEL, RÉMY MÜLLER, THOMAS HÉLIE and DAVID ROZE: Identification of Nonlinear Circuits As Port-Hamiltonian Systems | PIER PAOLO LA PASTINA, STEFANO D'ANGELO and LEONARDO GABRIELLI: Arbitrary-Order IIR Antiderivative Antialiasing | KURT JAMES WERNER: An Equivalent Circuit Interpretation of Antiderivative Antialiasing | MICHELE DUCCESCHI, STEFAN BILBAO and CRAIG J. WEBB: Non-Iterative Schemes for the Simulation of Nonlinear Audio Circuits | MOHAMMED DANISH, STEFAN BILBAO and MICHELE DUCCESCHI: Applications of Port Hamiltonian Methods to Non-Iterative Stable Simulations of the Korg35 and Moog 4-Pole VCF | FABIÁN ESQUEDA, BORIS KUZNETSOV AND JULIAN D. PARKER: Differentiable White-Box Virtual Analog Modeling | FRANÇOIS G. GERMAIN: Practical Virtual Analog Modeling Using Möbius Transforms | Session 2: Analysis and Manipulation: JASON NARADOWSKY: Amp-Space: A Large-Scale Dataset for Fine-Grained Timbre Transformation | JULIAN NERI, PHILIPPE DEPALLE and ROLAND BADEAU: Damped Chirp Mixture Estimation via Nonlinear Bayesian Regression | LEONARDO FIERRO and VESA VÄLIMÄKI: SiTraNo: A MATLAB App for Sines-Transients-Noise Decomposition of Audio Signals | MARCELO CAETANO and PHILIPPE DEPALLE: On the Estimation of Sinusoidal Parameters via Parabolic Interpolation of Scaled Magnitude Spectra | Session 3: Audio Processing and Effects: PIER PAOLO LA PASTINA and STEFANO D'ANGELO: Optimal Integer Order Approximation of Fractional Order Filters | CHAMP C. DARABUNDIT and JONATHAN S. ABEL: Conformal Maps for the Discretization of Analog Filters Near the Nyquist Limit | SEBASTIAN LAGUERRE and GARY P. SCAVONE: Simulating a Hexaphonic Pickup Using Parallel Comb Filters for Guitar Distortion | YURI DE PRA, FEDERICO FONTANA and STEFANO PAPETTI: Interacting with Digital Audio Effects Through a Haptic Knob with Programmable Resistance | SEBASTIAN ROSENZWEIG, SIMON SCHWÄR, JONATHAN DRIEDGER and MEINARD MÜLLER: Adaptive Pitch-Shifting with Applications to Intonati

Deep Brain Stimulation (DBS) is a surgical intervention that is known to reduce or eliminate the symptoms of common movement disorders, such as Parkinson.s disease, dystonia, or tremor. During the intervention the surgeon places electrodes inside of the patient.s brain to stimulate speci.c regions. Since these regions span only a couple of millimeters, and electrode misplacement has severe consequences, reliable and accurate navigation is of great importance. Usually the surgeon relies on fused CT and MRI data sets, as well as direct feedback from the patient. More recently Microelectrode Recordings (MER), which support navigation by measuring the electric .eld of the patient.s brain, are also used. We propose a visualization system that fuses the different modalities: imaging data, MER and patient checks, as well as the related uncertainties, in an intuitive way to present placement-related information in a consistent view with the goal of supporting the surgeon in the .nal placement of the stimulating electrode. We will describe the design considerations for our system, the technical realization, present the outcome of the proposed system, and provide an evaluation.

Fractal modulation is obtained by forming a power weighted superposition of scaled and modulated versions of the signal. The resulting signal is self-similar with fractal characteristics. In this paper we explore fractal modulation as a powerful method to generate rich signals, useful both for the synthesis of complex sounds, like the sounds from natural events or ecological sounds, or as control functions of audio effects. The wavelet transform can be used as an efficient tool in order to generate a subset of fractal modulated signals that are power homogeneous. Any signal used as a seed for fractal modulation is transformed into a multiscale sound by means of a tree-structured multirate filter bank. Moreover, by superimposing a structured modulation scheme one can generate pseudo-periodic sounds whose partials have fractal behavior.

In this paper we present a new method for denoising audio signals. The method is based on the Singular Value Decomposition (SVD) of the frame matrix representing the signal inthe Overlap Add decomposition. Denoising is performed by modifying both the singular values, using a tapering model, and the singular vectors of the representation, using a nonlinear PDE method. The performance of the method is evaluated and compared with denoising obtained by filtering.

In this paper we approach the synthesis of the slide guitar, which is a particular play mode of the guitar where continuous tuning of the tones is achieved by sliding a metal orglass piece, the bottleneck, along thestrings on the guitar neck side. The bottleneck constitues a unilateral constraint for the string vibration.Dynamics is subject to friction, scraping, textured displacement and collisions. The presented model is physically inspired and is based on a dynamic model of friction, together with a geometrical model of the textured displacements and a model for collisions of the string with the bottlenck. These models are suitablefor implementation in a digital waveguide computational scheme for the 3D vibration of the string, where continuous pitch bending is achieved by allpass filters to approximate fractional delays, friction is captured by nonlinear state-space systems in the slide junction and textured displacements by signal injection at avariable point in the waveguide.

In this paper, a model for the interaction of the strings with the frets in a guitar or other fretted string instruments is introduced. In the two-polarization representation of the string oscillations it is observed that the string interacts with the fret in different ways. While the vertical oscillation is governed by perfect or imperfect clamping of the string on the fret, the horizontal oscillation is subject to friction of the string over the surface of the fret. The proposed model allows, in particular, for the accurate evaluation of the elongation of the string in the two modes, which gives rise to audible dynamic detuning. The realization of this model into a structurally passive system for use in digital waveguide synthesis is detailed. By changing the friction parameters, the model can be employed in fretless instruments too, where the string directly interacts with the neck surface.

Perceptual auditory filter banks such as Bark-scale filter bank are widely used as front-end processing in speech recognition systems. However, the problem of the design of optimized filter banks that provide higher accuracy in recognition tasks is still open. Owing to spectral analysis in feature extraction, an adaptive bands filter bank (ABFB) is presented. The design adopts flexible bandwidths and center frequencies for the frequency responses of the filters and utilizes genetic algorithm (GA) to optimize the design parameters. The optimization process is realized by combining the front-end filter bank with the back-end recognition network in the performance evaluation loop. The deployment of ABFB together with zero-crossing peak amplitude (ZCPA) feature as a front process for radial basis function (RBF) system shows significant improvement in robustness compared with the Bark-scale filter bank. In ABFB, several sub-bands are still more concentrated toward lower frequency but their exact locations are determined by the performance rather than the perceptual criteria. For the ease of optimization, only symmetrical bands are considered here, which still provide satisfactory results., Funding Agencies|National Natural Science Foundation of China|61072087|Shanxi Provincial Graduate Innovation Fund of China|20093048

Physically inspired sound synthesis techniques have been devised for several instruments including guitar. Less well studied are methods to model the interactions of the player with strings and of the strings with other mechanical parts of the instrument. In this paper, we present methods based on simple scattering junctions to be inserted at various points along a digital waveguide simulating transversal wave propagation along a string. These junctions, which are derived using a balanced perturbation method for displacement wave variables, connect the waveguide with the external stimuli provided by the player or with objects that are part of the instrument. A model for plucking is revisited and improved. New nonlinear structures for the accurate model of collisions are developed. The proposed junctions achieve realistic synthesis of the interaction of the plucking finger or pick with the string, of the interaction of the fingers on the neck-side hand with strings, such as in the production of harmonics, and of the strings themselves with frets or fingerboard in a fretless instrument., ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Gianpaolo Evangelista and Fredrik Eckerholm, Player-Instrument Interaction Models for Digital Waveguide Synthesis of Guitar Touch and Collisions, 2010, IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, (18), 4, 822-832.http://dx.doi.org/10.1109/TASL.2009.2038822

The Oldenburg LOgatome speech corpus (OLLO) is specifically designed for evaluating speech recognition methods on variability. The performance of features carried on intrinsic variabilities in speech is meaningful for automatic speech recognition (ASR) system. ZCPA and MFCC were the two main features applied to OLLO French corpus in this paper. We took cepstral mean subtraction (CMS) on MFCC. Dynamic transforms (delta-delta-ZCPA and delta-delta-MFCC) were also adopted. The experiments show that the MFCC outperform the ZCPA in separate style. But ZCPA is more robust between different variabilities. The delta-delta operation of MFCC achieves best recognition in noise-free environment. Moreover, ZCPA could be complementary to MFCC so that one can combine them together especially on soft speaking style.

In this paper, we propose a binaural source localization method based on interaural time differences (ITDs) and interaural level differences (ILDs). The two cues, computed from a two-channel time-frequency representation, are combined in order to estimate the azimuth of sources in binaural recording. We introduce an individual parametric model for the ITD and ILD, and an average parametric model that sets us free from measurements of the subjects HRIRs for sound localization. We conduct several experiments to validate the proposed approach and show that it compares favorably with available techniques.

The filter bank in the front-end of a speech recognition system mimics the function of the basilar membrane. It is believed that the closer the band subdivision is to human perception, the better the recognition results. This paper proposes the use of Warped Filter Banks (WFBs) to replace traditional FIR filter banks and validates its use for the recognition of noisy speech. The WFBs bandwidths can be warped by using a first-order allpass transformation replacing the unit delay. Different warped factors in the allpass function can make the different scaled filter banks. Experiments carried on isolated words for speaker independent speech recognition show that the recognition rate with our proposed WFBs has been effectively increased.

In this paper, we provide a model of the plectrum, or guitar pick, for use in physically inspired sound synthesis. The model draws from the mechanics of beams. The profile of the plectrum is computed in real time based on its interaction with the string, which depends on the movement impressed by the player and the equilibrium of dynamical forces. A condition for the release of the string is derived, which allows to drive the digital waveguide simulating the string to the proper state at release time. The acoustic results are excellent, as verified in the sound examples provided.

Partial tracking in sinusoidal models have been studied for over twenty years now, and have been enhanced, making it precise and useful to analyse noiseless harmonic sounds. However, such tools have always been used in a monophonic (single channel) context. A method is thus proposed to adapt the partial tracking to the case of binaural signals. This gives a tool to perform spectral analysis of such signals, keeping relevant information from both left and right channels. Moreover, azimuth (position in the horizontal plane) information for each partial is gained using interaural cues, such as interaural time differences (ITDs) and interaural level differences (ILDs). The azimuth information can then be used as an attribute or as a constraint in the binaural partial tracking algorithm. Finally, some classification results using the azimuth of partials are presented.

Frequency warping is a desirable building block for sound effects and synthesis. Physical model driven pitch shifting of inharmonic sounds and the transformation of harmonic into inharmonic sounds are the main features of frequency warping effects. However, frequency warping sound signals is a non-causal and computationally expensive operation. In recent work [1] we showed that multirate filter bank s derived from a modified phase vocoder structure are suitable for the real-time approximate computation of frequency warping. The approximation is proven to be very accurate from both numerical and perceptual points of view. In this paper we extend the principles of the original design to implement time-varying frequency warping methods. The proposed algorithm is suitable for inclusion in the synthesis of systems with dynamic stiffness and for the production of captivating audio effects.

In this paper the problem of the synthesis of plucked strings by means of physically inspired models is reconsidered in the context of the player-s interaction with the virtual instrument. While solutions for the synthesis of guitar tones have been proposed, which are excellent from the acoustic point of view, the problem of the control of the physical parameters directly by the player has not received sufficient attention. In this paper we revive a simple model previously presented by Cuzzucoli and Lombardo for the player-s touch. We show that the model is affected by an inconsistency that can be removed by introducing the finger/pick perturbation in a balanced form on the digital waveguide. The results, together with a more comprehensive model of the guitar have been implemented in a VST plugin, which is the starting point for further research.