Soft Sound: a Guide to the Tools and Techniques of Software Synthesis
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Integer-Based Wavetable Synthesis for Low-Computational Embedded Systems Ben Wright and Somsak Sukittanon University of Tennessee at Martin Department of Engineering Martin, TN USA [email protected], [email protected] Abstract— The evolution of digital music synthesis spans from discussed. Section B will discuss the mathematics explaining tried-and-true frequency modulation to string modeling with the components of the wavetables. Part II will examine the neural networks. This project begins from a wavetable basis. music theory used to derive the wavetables and the software The audio waveform was modeled as a superposition of formant implementation. Part III will cover the applied results. sinusoids at various frequencies relative to the fundamental frequency. Piano sounds were reverse-engineered to derive a B. Mathematics and Music Theory basis for the final formant structure, and used to create a Many periodic signals can be represented by a wavetable. The quality of reproduction hangs in a trade-off superposition of sinusoids, conventionally called Fourier between rich notes and sampling frequency. For low- series. Eigenfunction expansions, a superset of these, can computational systems, this calls for an approach that avoids represent solutions to partial differential equations (PDE) burdensome floating-point calculations. To speed up where Fourier series cannot. In these expansions, the calculations while preserving resolution, floating-point math was frequency of each wave (here called a formant) in the avoided entirely--all numbers involved are integral. The method was built into the Laser Piano. Along its 12-foot length are 24 superposition is a function of the properties of the string. This “keys,” each consisting of a laser aligned with a photoresistive is said merely to emphasize that the response of a plucked sensor connected to 8-bit MCU. -
Granular Synthesis and Physical Modeling with This Manual Is Released Under the Creative Commons Attribution 3.0 Unported License
Granular synthesis and physical modeling with This manual is released under the Creative Commons Attribution 3.0 Unported License. You may copy, distribute, transmit and adapt it, for any purpose, provided you include the following attribution: Kaivo and the Kaivo manual by Madrona Labs. http://madronalabs.com. Version 1.3, December 2016. Written by George Cochrane and Randy Jones. Illustrated by David Chandler. Typeset in Adobe Minion using the TEX document processing system. Any trademarks mentioned are the sole property of their respective owners. Such mention does not imply any endorsement of or associa- tion with Madrona Labs. Introduction “The future evolution of virtual devices is less constrained than that of real devices.” –Julius O. Smith Kaivo is a software instrument combining two powerful synthesis techniques (physical modeling and granular synthesis) in an easy-to- use semi-modular package. It’s laid out a bit like an acoustic instru- For more information on the theory be- ment; the GRANULATOR module acts like the player’s touch, exciting hind Kaivo, see Chapter 1, “Physi-who? Granu-what?” one or more tuned objects (here, the RESONATOR module, based on physical models of resonant objects) that come together in a central resonating body (the BODY module, also physics-based). This allows for a natural (or uncanny) sense of space, pleasing in- teractions between voices, and a ton of expressive potential—all traits in short supply in digital synthesis. The acoustic comparison begins to pale when you realize that your “touch” is really a granular sam- ple player with scads of options, and that the physical properties of the resonating modules are widely variable, and in real time. -
Vector Synthesis: a Media Archaeological Investigation Into Sound-Modulated Light
VECTOR SYNTHESIS: A MEDIA ARCHAEOLOGICAL INVESTIGATION INTO SOUND-MODULATED LIGHT Submitted for the qualification Master of Arts in Sound in New Media, Department of Media, Aalto University, Helsinki FI April, 2019 Supervisor: Antti Ikonen Advisor: Marco Donnarumma DEREK HOLZER [BLANK PAGE] Aalto University, P.O. BOX 11000, 00076 AALTO www.aalto.fi Master of Arts thesis abstract Author Derek Holzer Title of thesis Vector Synthesis: a Media-Archaeological Investigation into Sound-Modulated Light Department Department of Media Degree programme Sound in New Media Year 2019 Number of pages 121 Language English Abstract Vector Synthesis is a computational art project inspired by theories of media archaeology, by the history of computer and video art, and by the use of discarded and obsolete technologies such as the Cathode Ray Tube monitor. This text explores the military and techno-scientific legacies at the birth of modern computing, and charts attempts by artists of the subsequent two decades to decouple these tools from their destructive origins. Using this history as a basis, the author then describes a media archaeological, real time performance system using audio synthesis and vector graphics display techniques to investigate direct, synesthetic relationships between sound and image. Key to this system, realized in the Pure Data programming environment, is a didactic, open source approach which encourages reuse and modification by other artists within the experimental audiovisual arts community. Keywords media art, media-archaeology, audiovisual performance, open source code, cathode- ray tubes, obsolete technology, synesthesia, vector graphics, audio synthesis, video art [BLANK PAGE] O22 ABSTRACT Vector Synthesis is a computational art project inspired by theories of media archaeology, by the history of computer and video art, and by the use of discarded and obsolete technologies such as the Cathode Ray Tube monitor. -
The Sonification Handbook Chapter 9 Sound Synthesis for Auditory Display
The Sonification Handbook Edited by Thomas Hermann, Andy Hunt, John G. Neuhoff Logos Publishing House, Berlin, Germany ISBN 978-3-8325-2819-5 2011, 586 pages Online: http://sonification.de/handbook Order: http://www.logos-verlag.com Reference: Hermann, T., Hunt, A., Neuhoff, J. G., editors (2011). The Sonification Handbook. Logos Publishing House, Berlin, Germany. Chapter 9 Sound Synthesis for Auditory Display Perry R. Cook This chapter covers most means for synthesizing sounds, with an emphasis on describing the parameters available for each technique, especially as they might be useful for data sonification. The techniques are covered in progression, from the least parametric (the fewest means of modifying the resulting sound from data or controllers), to the most parametric (most flexible for manipulation). Some examples are provided of using various synthesis techniques to sonify body position, desktop GUI interactions, stock data, etc. Reference: Cook, P. R. (2011). Sound synthesis for auditory display. In Hermann, T., Hunt, A., Neuhoff, J. G., editors, The Sonification Handbook, chapter 9, pages 197–235. Logos Publishing House, Berlin, Germany. Media examples: http://sonification.de/handbook/chapters/chapter9 18 Chapter 9 Sound Synthesis for Auditory Display Perry R. Cook 9.1 Introduction and Chapter Overview Applications and research in auditory display require sound synthesis and manipulation algorithms that afford careful control over the sonic results. The long legacy of research in speech, computer music, acoustics, and human audio perception has yielded a wide variety of sound analysis/processing/synthesis algorithms that the auditory display designer may use. This chapter surveys algorithms and techniques for digital sound synthesis as related to auditory display. -
Combining Granular Synthesis with Frequency Modulation
Combining granular synthesis with frequency modulation. Kim ERVIK Øyvind BRANDSEGG Department of music Department of music University of Science and Technology University of Science and Technology Norway Norway [email protected] [email protected] Abstract acoustical events. Sound as particles has been Both granular synthesis and frequency used in applications like independent time and modulation are well-established synthesis pitch scaling, formant modification, analog synth techniques that are very flexible. This paper modeling, clouds of sound, granular delays and will investigate different ways of combining reverbs, etc [3]. Examples of granular synthesis the two techniques. It will describe the rules parameters are density, grain pitch, grain duration, of spectra that emerge when combining, compare it to similar synthesis techniques and grain envelope, the global arrangement of the suggest some aesthetic perspectives on the grains, and of course the content of the grains matter. (which can be a synthetic waveform or sampled sound). Granular synthesis gives the musician vast Keywords expressive possibilities [10]. Granular synthesis, frequency modulation, 1.3 FM synthesis partikkel, csound, sound synthesis Frequency modulation has been a known method of coding audio into radio signal since the beginning of commercial radio. In 1964 that John Chowning discovered the implication of frequency modulation of audio working on synthesis of brass instrument at Stanford [2]. He discovered that modulating the frequency resulted in sideband emerging from the carrier frequency. Fig 1:Grain Pitch modulation Yamaha later implemented the technique in the hugely successful DX7. 1 Introduction If we consider FM synthesis using sinusoidal carrier and modulation oscillator, the spectral 1.1 Method components present in a FM sound can be mathematically stated as in figure 2. -
Wavetable Synthesis 101, a Fundamental Perspective
Wavetable Synthesis 101, A Fundamental Perspective Robert Bristow-Johnson Wave Mechanics, Inc. 45 Kilburn St., Burlington VT 05401 USA [email protected] ABSTRACT: Wavetable synthesis is both simple and straightforward in implementation and sophisticated and subtle in optimization. For the case of quasi-periodic musical tones, wavetable synthesis can be as compact in data storage requirements and as general as additive synthesis but requires much less real-time computation. This paper shows this equivalence, explores some suboptimal methods of extracting wavetable data from a recorded tone, and proposes a perceptually relevant error metric and constraint when attempting to reduce the amount of stored wavetable data. 0 INTRODUCTION Wavetable music synthesis (not to be confused with common PCM sample buffer playback) is similar to simple digital sine wave generation [1] [2] but extended at least two ways. First, the waveform lookup table contains samples for not just a single period of a sine function but for a single period of a more general waveshape. Second, a mechanism exists for dynamically changing the waveshape as the musical note evolves, thus generating a quasi-periodic function in time. This mechanism can take on a few different forms, probably the simplest being linear crossfading from one wavetable to the next sequentially. More sophisticated methods are proposed by a few authors (recently Horner, et al. [3] [4]) such as mixing a set of well chosen basis wavetables each with their corresponding envelope function as in Fig. 1. The simple linear crossfading method can be thought of as a subclass of the more general basis mixing method where the envelopes are overlapping triangular pulse functions. -
Computer Sound Design : Synthesis Techniques and Programming
Computer Sound Design Titles in the Series Acoustics and Psychoacoustics, 2nd edition (with website) David M. Howard and James Angus The Audio Workstation Handbook Francis Rumsey Composing Music with Computers (with CD-ROM) Eduardo Reck Miranda Digital Audio CD and Resource Pack Markus Erne (Digital Audio CD also available separately) Digital Sound Processing for Music and Multimedia (with website) Ross Kirk and Andy Hunt MIDI Systems and Control, 2nd edition Francis Rumsey Network Technology for Digital Audio Andrew Bailey Computer Sound Design: Synthesis techniques and programming, 2nd edition (with CD-ROM) Eduardo Reck Miranda Sound and Recording: An introduction, 4th edition Francis Rumsey and Tim McCormick Sound Synthesis and Sampling Martin Russ Sound Synthesis and Sampling CD-ROM Martin Russ Spatial Audio Francis Rumsey Computer Sound Design Synthesis techniques and programming Second edition Eduardo Reck Miranda Focal Press An imprint of Elsevier Science Linacre House, Jordan Hill, Oxford OX2 8DP 225 Wildwood Avenue, Woburn MA 01801-2041 First published as Computer Sound Synthesis for the Electronic Musician 1998 Second edition 2002 Copyright © 1998, 2002, Eduardo Reck Miranda. All rights reserved The right of Eduardo Reck Miranda to be identified as the author of this work has been asserted in accordance with the Copyright, Designs and Patents Act 1988 No part of this publication may be reproduced in any material form (including photocopying or storing in any medium by electronic means and whether or not transiently or incidentally to some other use of this publication) without the written permission of the copyright holder except in accordance with the provisions of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency Ltd, 90 Tottenham Court Road, London, England W1T 4LP. -
Neural Granular Sound Synthesis
Neural Granular Sound Synthesis Adrien Bitton Philippe Esling Tatsuya Harada IRCAM, CNRS UMR9912 IRCAM, CNRS UMR9912 The University of Tokyo, RIKEN Paris, France Paris, France Tokyo, Japan [email protected] [email protected] [email protected] ABSTRACT Granular sound synthesis is a popular audio generation technique based on rearranging sequences of small wave- resynthesis generated sequence match decode form windows. In order to control the synthesis, all grains grains in a given corpus are analyzed through a set of acoustic continuous + f(↵) descriptors. This provides a representation reflecting some discrete + condition + form of local similarities across the grains. However, the grain space + quality of this grain space is bound by that of the descrip- + + + grain tors. Its traversal is not continuously invertible to signal grain + + latent space sample and does not render any structured temporality. library dz acoustic R We demonstrate that generative neural networks can im- analysis encode plement granular synthesis while alleviating most of its target signal shortcomings. We efficiently replace its audio descriptor input basis by a probabilistic latent space learned with a Vari- signal ational Auto-Encoder. In this setting the learned grain space is invertible, meaning that we can continuously syn- thesize sound when traversing its dimensions. It also im- Figure 1. Left: A grain library is analysed and scattered (+) into the acoustic dimensions. A target is defined, by analysing an other signal (o) plies that original grains are not stored for synthesis. An- or as a free trajectory, and matched to the library through the acoustic other major advantage of our approach is to learn struc- descriptors. -
Pdf Nord Modular
Table of Contents 1 Introduction 1.1 The Purpose of this Document 1.2 Acknowledgements 2 Oscillator Waveform Modification 2.1 Sync 2.2 Frequency Modulation Techniques 2.3 Wave Shaping 2.4 Vector Synthesis 2.5 Wave Sequencing 2.6 Audio-Rate Crossfading 2.7 Wave Terrain Synthesis 2.8 VOSIM 2.9 FOF Synthesis 2.10 Granular Synthesis 3 Filter Techniques 3.1 Resonant Filters as Oscillators 3.2 Serial and Parallel Filter Techniques 3.3 Audio-Rate Filter Cutoff Modulation 3.4 Adding Analog Feel 3.5 Wet Filters 4 Noise Generation 4.1 White Noise 4.2 Brown Noise 4.3 Pink Noise 4.4 Pitched Noise 5 Percussion 5.1 Bass Drum Synthesis 5.2 Snare Drum Synthesis 5.3 Synthesis of Gongs, Bells and Cymbals 5.4 Synthesis of Hand Claps 6 Additive Synthesis 6.1 What is Additive Synthesis? 6.2 Resynthesis 6.3 Group Additive Synthesis 6.4 Morphing 6.5 Transients 6.7 Which Oscillator to Use 7 Physical Modeling 7.1 Introduction to Physical Modeling 7.2 The Karplus-Strong Algorithm 7.3 Tuning of Delay Lines 7.4 Delay Line Details 7.5 Physical Modeling with Digital Waveguides 7.6 String Modeling 7.7 Woodwind Modeling 7.8 Related Links 8 Speech Synthesis and Processing 8.1 Vocoder Techniques 8.2 Speech Synthesis 8.3 Pitch Tracking 9 Using the Logic Modules 9.1 Complex Logic Functions 9.2 Flipflops, Counters other Sequential Elements 9.3 Asynchronous Elements 9.4 Arpeggiation 10 Algorithmic Composition 10.1 Chaos and Fractal Music 10.2 Cellular Automata 10.3 Cooking Noodles 11 Reverb and Echo Effects 11.1 Synthetic Echo and Reverb 11.2 Short-Time Reverb 11.3 Low-Fidelity -
Wavetable FM Synthesizer [RACK EXTENSION] MANUAL
WTFM Wavetable FM Synthesizer [RACK EXTENSION] MANUAL 2021 by Turn2on Software WTFM is not an FM synthesizer in the traditional sense. Traditional Wavetable (WT) synthesis. 4 oscillators, Rather it is a hybrid synthesizer which uses the each including 450+ Wavetables sorted into flexibility of Wavetables in combination with FM categories. synthesizer Operators. Classical 4-OP FM synthesis: each operator use 450+ WTFM Wavetable FM Synthesizer produces complex Wavetables to modulate other operators in various harmonics by modulating the various selectable WT routing variations of 24 FM Algorithms. waveforms of the oscillators using further oscillators FM WT Mod Synthesis: The selected Wavetable (operators). modulates the frequency of the FM Operators (Tune / Imagine the flexibility of the FM Operators using this Ratio). method. Wavetables are a powerful way to make FM RINGMOD Synthesis: The selected Wavetable synthesis much more interesting. modulates the Levels of the FM Operators similarly to a RingMod WTFM is based on the classical Amp, Pitch and Filter FILTER FM Synthesis: The selected Wavetable Envelopes with AHDSR settings. PRE and POST filters modulates the Filter Frequency of the synthesizer. include classical HP/BP/LP modes. 6 FXs (Vocoder / EQ Band / Chorus / Delay / Reverb) plus a Limiter which This is a modern FM synthesizer with easy to program adds total control for the signal and colours of the traditional AHDSR envelopes, four LFO lines, powerful Wavetable FM synthesis. modulations, internal effects, 24 FM algorithms. Based on the internal wavetable's library with rich waveform Operators Include 450+ Wavetables (each 64 content: 32 categories, 450+ wavetables (each with 64 singlecycle waveforms) all sorted into individual single-cycle waveforms), up to 30,000 waveforms in all. -
Concatenative Sound Synthesis: the Early Years
CONCATENATIVE SOUND SYNTHESIS: THE EARLY YEARS Diemo Schwarz Ircam – Centre Pompidou 1, place Igor-Stravinsky, 75003 Paris, France http://www.ircam.fr/anasyn/schwarz http://concatenative.net [email protected] ABSTRACT Concatenative sound synthesis (CSS) methods use a large database of source sounds, segmented into units, Concatenative sound synthesis is a promising method and a unit selection algorithm that finds the sequence of of musical sound synthesis with a steady stream of work units that match best the sound or phrase to be synthe- and publications for over five years now. This article of- sised, called the target. The selection is performed ac- fers a comparative survey and taxonomy of the many dif- cording to the descriptors of the units, which are charac- ferent approaches to concatenative synthesis throughout teristics extracted from the source sounds, or higher level the history of electronic music, starting in the 1950s, even descriptors attributed to them. The selected units can then if they weren't known as such at their time, up to the recent be transformed to fully match the target specification, and surge of contemporary methods. Concatenative sound are concatenated. However, if the database is sufficiently synthesis methods use a large database of source sounds, large, the probability is high that a matching unit will be segmented into units, and a unit selection algorithm that found, so the need to apply transformations, which always finds the units that match best the sound or musical phrase degrade sound quality, is reduced. The units can be non- to be synthesised, called the target. The selection is per- uniform (heterogeneous), i.e. -
Chroma Palette: Chromatic Maps of Sound As Granular Synthesis
Proceedings of the 2007 Conference on New Interfaces for Musical Expression (NIME07), New York, NY, USA Chroma Palette: Chromatic Maps of Sound As Granular Synthesis Interface Justin Donaldson Ian Knopke Chris Raphael Indiana University School of Indiana University School of Indiana University School of Informatics Informatics Informatics 1900 E. 10th Street, Room 931 1900 E. 10th Street, Room 932 1900 E. 10th Street, Room 933 Bloomington, IN 47406 Bloomington, IN 47406 Bloomington, IN 47406 [email protected] [email protected] [email protected] ABSTRACT There are many different categories of granular synthesis, Chroma based representations of acoustic phenomenon are such as synchronous, quasi-synchronous, and asynchronous representations of sound as pitched acoustic energy. A frame- forms, referring to the regularity with which grains are wise chroma distribution over an entire musical piece is a useful reassembled. Grains are usually windowed, both to aid resynthesis and straightforward representation of its musical pitch over time. and to avoid audible clicks. However, the choice of window This paper examines a method of condensing the block-wise function can also have a pronounced effect on the resulting timbre chroma information of a musical piece into a two dimensional and is an important component of the synthesis process. Granular embedding. Such an embedding is a representation or map of the synthesis has similarities to other common analysis/resynthesis different pitched energies in a song, and how these energies relate methodologies such as the short-term Fourier transform and to each other in the context of the song. The paper presents an wavelet-based techniques. Figure 1 shows an example of an interactive version of this representation as an exploratory envelope windowing and overlap arrangement for four different analytical tool or instrument for granular synthesis.