Toward Synthesized Environments: A Survey of Analysis and Synthesis Methods

for Sound Designers and Composers

Ananya Misra, Perry Cook

Princeton University

Motivation

• Multitude of sounds in the sonic landscape• Multitude of algorithms• Better knowledge of a variety of algorithms

=> empowerment to create rich sound scenes

Some Related Surveys

• Smith. “Viewpoints on the History of Digital Synthesis.” ICMC 1991.

• Pope. “A Taxonomy of Computer Music.” Contemporary Music Review 1996.

• Tolonen et al. “Evaluation of Modern Sound Synthesis Methods.” Tech. Rep. 1998.

• Vercoe et al. “Structured Audio: Creation, Transmission, and Rendering of Parametric Sound Representations.” Proc. IEEE 1998.

• Widmer et al. “Sound and Music Computing: Research Trends and Some Key Issues.” JNMR 2007.

This one: from the perspective of creating complex environmental sound scenes or compositions

Overview

• Abstract synthesis algorithms• Synthesis from “scratch”• Synthesis from existing sounds

– Concatenative techniques– Additive synthesis– Subtractive synthesis and other techniques

• Analysis not for synthesis

Disclaimer: No taxonomy is clean or 1-1 from method to class

Abstract synthesis algorithms

Oscillators

• From analog days

Sine wave Triangle wave Sawtooth wave

Alarm clock

Examples by ChucK

Frequency Modulation

• Modulation of one oscillator’s phase by another’s output

Basic example

Doorbells

Examples by ChucK

More

• Circle maps as nonlinear oscillators (Essl, ICMC 2006)

• Errant sound synthesis: “the potential of any algorithm cast into the audio range” (Collins, ICMC 2008)

• Auditory display and sonification

Synthesis from scratch

Synthesis from physical or perceptual models, without the raw material of

existing audio samples

Physical models

High-level parametric control over synthesized sound

• Plucked string model, waveguides and more• Reed and bowstring models, singing voice

synthesis, percussive sounds• Synthesis ToolKit => PeRColate (Max/MSP),

ChucK, SuperCollider• Real-world contact / motion sounds

Modal synthesis Gait modelingCook, 2002

Perceptual models

Give desired perceptual characteristics• For speech and singing (Cook, CMJ 1996):

– Formant synthesizers– Formant wave functions (FOFs) (Rodet,

CMJ 1984) • General: Feature-based synthesis (Hoffman,

ICMC 2006)

=>

Synthesis from existing sounds

Creation of sound from existing sound, synthesis by analysis

Concatenative techniques

• Rearrangement of samples in the time domain

• Wavetable synthesis• Concatenative synthesis (Schwarz, JNMR

2006):– Source sound segmented into units– Target sound– Set of unit descriptors– Unit selection algorithm

Concatenative techniques

• Applications: singing, instruments, audio mosaicing

• Granular synthesis: concatenating usually short “sound grains” (Truax, 1990)

Concatenative techniques: granular synthesis

• Formant wave functions, when using arbitrary sound samples

• Dictionary-based methods with time-localized waveforms (Sturm, ICMC 2008) => analytical counterpart

• TAPESTREA: granular synthesis by parametrically looping transformed events

Concatenative techniques for sound textures

• Splitting soundscapes into syllable-like segments (Hoskinson, ICMC 2001)

• Soundscape generation from database of annotated sound files (Birchfield, ICMC 2005)

• Fast sound texture synthesis using overlap-add (Fröjd, ICMC 2007)

From Fröjd&Horner, 2007;algorithm offered in TAPESTREA

Additive synthesis

Spectral analysis, addition of resulting signals

• Channel vocoder: bank of bandpass filters• Phase vocoder: FFT to get phase as well as

magnitude of each frequency band• Pitch and time transformations (offered in

TAPESTREA)• Cross-synthesis

Additive synthesis: sinusoidal modeling

• Speech signals can be modeled using a few sinusoids (McAulay 1986, Quatieri 1986)

• Spectral modeling synthesis (Serra, 1989): sines + noise

• Lemur/Loris, CLAM, SMS, SPEAR, AudioSculpt• Used to extract and transform some

environmental sounds in TAPESTREA

Transformed windchimes Baby chorus / cacophony

Sines + Transients + Noise

Decompose into transients (brief, noisy events) as well as sines and noise

• Transient / onset detection techniques:– Time-domain envelope following (in TAPESTREA)– Comparing energy envelopes of original and

residual noise signals (Levine, 1998)– Comparing energy in short and long signal

segments (Verma, 1998) (in TAPESTREA)– Frequency-domain techniques

Subtractive synthesis and linear predictive coding

• Filtering a signal to shape it by subtracting unwanted components

• LPC: Source-filter model where next = linear combination of previous samples (Atal, 1970)

• Musical composition (Lansky, 1989)• Sound texture synthesis (Athineos, 2003;

Zhu, 2004)

Noise-excited LPCTime-frequency LPC;Athineos&Ellis, 2003

Other tools for sound textures

• Wavelet-tree learning (Dubnov, 2002) (offered in TAPESTREA)

• Parametrically modeling and transforming stochastic components (Miner, 2002)

• Inferring statistical distributions of events (Zhu, 2003)

Analysis not for synthesis

Content-based analysis methods not necessarily designed for synthesis. May provide information to guide

synthesis algorithms.

Analyze to…

• Represent an audio signal in structurally or perceptually meaningful ways

• Understand and use a collection of sounds on a global level

Representing a signal

• Source separation: Computational auditory scene analysis (Ellis, 1992; Melih, 2000)– Automatic and manual grouping of partials offered

in TAPESTREA

• Source separation: Multiple fundamental frequency estimation (Klapuri, 2004)

• Blind source separation (Hoffman, 2009)• Music transcription

Understanding a collection

• Comparison actions: content-based classification, search, recommendation, …

• Automatic timbre recognition• Music information retrieval tools, e.g.

MARSYAS

Conclusions

Advantages of parametric synthesis algorithms

• Many algorithms may contribute to one simple piece

• Many available tools: programming languages, specialized libraries, graphical software

• Compression• Ability to re-render over and over with

changes, interactively or in real-time• Rich palette of techniques for composers

Taxonomy of methods by soundsSound/Goal Methods

Abstract FM, non-linear oscillators, feature-based synthesis, wavetables, granular synthesis

Acoustic instruments Wavetables, waveguides / physical models, granular synthesis, additive synthesis

Contact sounds Physical models

Cross-synthesis LPC, vocoders

Pitch/time transformations

LPC, vocoders, granular synthesis, additive synthesis

Pitched sounds Additive synthesis, granular synthesis, FM, oscillators

Singing voice FM, formant synthesis, FOFs, granular synthesis, additive synthesis

Speech Formant synthesis, FOFs, granular synthesis, vocoders, additive synthesis, LPC

Textures and soundscapes

Granular synthesis, LPC, stochastic and wavelet-based methods

Transients Onset detection, physical models, granular synthesis, sines+transients+noise models