A nonlinear digital model of the EMS VCS3 voltage-controlled filter

This article presents a nonlinear discrete-time model of the EMS VCS3 voltage-controlled filters. The development of the model is based on the study of the filter circuitry and its behavior in the time domain. From this circuitry a system of nonlinear differential equations has been derived describing the dynamics in regime of large signals. The digital implementation of the filter is based on a numerical approximation of those equations. The resulting Matlab model has been compared with a structurally identical simulation running under PSpice. Finally, a real-time realization of the VCF has been implemented under the Pure Data processing environment

Wave digital modeling of the diode-based ring modulator

The ring modulator is a strongly nonlinear circuit common in audio gear, especially as part of electronic musical instruments. In this paper, an accurate model based on Wave Digital (WD) principles is developed for implementing the ring modulator as a digital audio effect. The reference circuit is constituted of four diodes and two multi-winding transformers. The proposed WD implementation is based on the Scattering Iterative Method (SIM), recently developed for the static analysis of large nonlinear photovoltaic arrays. In this paper, SIM is shown to be suitable for implementing also audio circuits for Virtual Analog applications, such as the ring modulator, since it is stable, robust and comparable to or more efficient than state-of-the-art strategies in terms of computational cost

Learning Parameter Spaces in Neural Modeling of Audio Circuits

This thesis studies black-box virtual analog modeling formulated as a machine learning sequence modeling task within the category of supervised learning problems. The focus is on learning scenarios where the modeling targets have multiple user controls, and the aim of the thesis is to evaluate how the properties of the training datasets affect the generalization of the learning algorithm. To study the problem, three nonlinear analogue sound processors were modeled using a recurrent neural network consisting of a Gated Recurrent Unit and a fully-connected output layer. For each target device, two groups of datasets, seven in total, were constructed, using SPICE simulations of the targets. The difference between the datasets is in the density of the sampling grid used for setting the user controls of the targets, as well as in the number of input/output pairs corresponding to each distinct value of each of the controls. For the targets considered during the study, the sparsest sampling grid using only three possible values for each of the user controls was found inadequate for the models to generalize over the testsets used for evaluation. Increasing the sampling density was seen improving the model performance in most cases, with some targets also portraying clear advantages with increasing the number of input/output pairs corresponding to each distinct value of the user controls. According to the study, a sampling grid with five points would appear as a good baseline for training neural networks on targets with multiple user controls when no further investigations in the sampling density can be afforded. For future work, the experiments could be extended to include global scaling of the dataset size while keeping the constraints for sampling the parameter spaces, as well as combining the data generation and training procedures to a single loop, allowing for potentially infinite variety within the datasets

Real-time sound synthesis on a multi-processor platform

Real-time sound synthesis means that the calculation and output of each sound sample for a channel of audio information must be completed within a sample period. At a broadcasting standard, a sampling rate of 32,000 Hz, the maximum period available is 31.25 μsec. Such requirements demand a large amount of data processing power. An effective solution for this problem is a multi-processor platform; a parallel and distributed processing system. The suitability of the MIDI [Music Instrument Digital Interface] standard, published in 1983, as a controller for real-time applications is examined. Many musicians have expressed doubts on the decade old standard's ability for real-time performance. These have been investigated by measuring timing in various musical gestures, and by comparing these with the subjective characteristics of human perception. An implementation and its optimisation of real-time additive synthesis programs on a multi-transputer network are described. A prototype 81-polyphonic-note- organ configuration was implemented. By devising and deploying monitoring processes, the network's performance was measured and enhanced, leading to an efficient usage; the 88-note configuration. Since 88 simultaneous notes are rarely necessary in most performances, a scheduling program for dynamic note allocation was then introduced to achieve further efficiency gains. Considering calculation redundancies still further, a multi-sampling rate approach was applied as a further step to achieve an optimal performance. The theories underlining sound granulation, as a means of constructing complex sounds from grains, and the real-time implementation of this technique are outlined. The idea of sound granulation is quite similar to the quantum-wave theory, "acoustic quanta". Despite the conceptual simplicity, the signal processing requirements set tough demands, providing a challenge for this audio synthesis engine. Three issues arising from the results of the implementations above are discussed; the efficiency of the applications implemented, provisions for new processors and an optimal network architecture for sound synthesis

Designing sound : procedural audio research based on the book by Andy Farnell

In procedural media, data normally acquired by measuring something, commonly described as sampling, is replaced by a set of computational rules (procedure) that defines the typical structure and/or behaviour of that thing. Here, a general approach to sound as a definable process, rather than a recording, is developed. By analysis of their physical and perceptual qualities, natural objects or processes that produce sound are modelled by digital Sounding Objects for use in arts and entertainments. This Thesis discusses different aspects of Procedural Audio introducing several new approaches and solutions to this emerging field of Sound Design.Em Media Procedimental, os dados os dados normalmente adquiridos através da medição de algo habitualmente designado como amostragem, são substituídos por um conjunto de regras computacionais (procedimento) que definem a estrutura típica, ou comportamento, desse elemento. Neste caso é desenvolvida uma abordagem ao som definível como um procedimento em vez de uma gravação. Através da análise das suas características físicas e perceptuais , objetos naturais ou processos que produzem som, são modelados como objetos sonoros digitais para utilização nas Artes e Entretenimento. Nesta Tese são discutidos diferentes aspectos de Áudio Procedimental, sendo introduzidas várias novas abordagens e soluções para o campo emergente do Design Sonoro

Making music through real-time voice timbre analysis: machine learning and timbral control

PhDPeople can achieve rich musical expression through vocal sound { see for example human beatboxing, which achieves a wide timbral variety through a range of extended techniques. Yet the vocal modality is under-exploited as a controller for music systems. If we can analyse a vocal performance suitably in real time, then this information could be used to create voice-based interfaces with the potential for intuitive and ful lling levels of expressive control. Conversely, many modern techniques for music synthesis do not imply any particular interface. Should a given parameter be controlled via a MIDI keyboard, or a slider/fader, or a rotary dial? Automatic vocal analysis could provide a fruitful basis for expressive interfaces to such electronic musical instruments. The principal questions in applying vocal-based control are how to extract musically meaningful information from the voice signal in real time, and how to convert that information suitably into control data. In this thesis we address these questions, with a focus on timbral control, and in particular we develop approaches that can be used with a wide variety of musical instruments by applying machine learning techniques to automatically derive the mappings between expressive audio input and control output. The vocal audio signal is construed to include a broad range of expression, in particular encompassing the extended techniques used in human beatboxing. The central contribution of this work is the application of supervised and unsupervised machine learning techniques to automatically map vocal timbre to synthesiser timbre and controls. Component contributions include a delayed decision-making strategy for low-latency sound classi cation, a regression-tree method to learn associations between regions of two unlabelled datasets, a fast estimator of multidimensional di erential entropy and a qualitative method for evaluating musical interfaces based on discourse analysis

Evaluation Methodologies in Software Protection Research

Man-at-the-end (MATE) attackers have full control over the system on which the attacked software runs, and try to break the confidentiality or integrity of assets embedded in the software. Both companies and malware authors want to prevent such attacks. This has driven an arms race between attackers and defenders, resulting in a plethora of different protection and analysis methods. However, it remains difficult to measure the strength of protections because MATE attackers can reach their goals in many different ways and a universally accepted evaluation methodology does not exist. This survey systematically reviews the evaluation methodologies of papers on obfuscation, a major class of protections against MATE attacks. For 572 papers, we collected 113 aspects of their evaluation methodologies, ranging from sample set types and sizes, over sample treatment, to performed measurements. We provide detailed insights into how the academic state of the art evaluates both the protections and analyses thereon. In summary, there is a clear need for better evaluation methodologies. We identify nine challenges for software protection evaluations, which represent threats to the validity, reproducibility, and interpretation of research results in the context of MATE attacks

Abstracts from the 50th European Society of Human Genetics Conference: Posters

International audienc