1. Toward Synthesized Environments: A Survey of Analysis and Synthesis Methods for Sound Designers and Composers Ananya Misra, Perry Cook Princeton University

2. Motivation Multitude of sounds in the sonic landscape Multitude of algorithms Better knowledge of a variety of algorithms => empowerment to create rich sound scenes

3. 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

4. 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

5. Abstract synthesis algorithms

6. Oscillators From analog days Sine waveTriangle waveSawtooth wave Alarm clock Examples by ChucK

7. Frequency Modulation Modulation of one oscillator’s phase by another’s output Basic example Doorbells Examples by ChucK

8. 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

9. Synthesis from scratch Synthesis from physical or perceptual models, without the raw material of existing audio samples

10. 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 synthesisGait modeling Cook, 2002

11. 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) =>

12. Synthesis from existing sounds Creation of sound from existing sound, synthesis by analysis

13. 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

14. Concatenative techniques Applications: singing, instruments, audio mosaicing Granular synthesis: concatenating usually short “sound grains” (Truax, 1990)

15. 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

16. 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

17. 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

18. 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 windchimesBaby chorus / cacophony

19. 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

20. 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 LPC Time-frequency LPC; Athineos&Ellis, 2003

21. 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)

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

23. Analyze to… Represent an audio signal in structurally or perceptually meaningful ways Understand and use a collection of sounds on a global level

24. 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

25. Understanding a collection Comparison actions: content-based classification, search, recommendation, … Automatic timbre recognition Music information retrieval tools, e.g. MARSYAS

26. Conclusions

27. 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

28. Taxonomy of methods by sounds Sound/GoalMethods AbstractFM, non-linear oscillators, feature-based synthesis, wavetables, granular synthesis Acoustic instrumentsWavetables, waveguides / physical models, granular synthesis, additive synthesis Contact soundsPhysical models Cross-synthesisLPC, vocoders Pitch/time transformations LPC, vocoders, granular synthesis, additive synthesis Pitched soundsAdditive synthesis, granular synthesis, FM, oscillators Singing voiceFM, formant synthesis, FOFs, granular synthesis, additive synthesis SpeechFormant synthesis, FOFs, granular synthesis, vocoders, additive synthesis, LPC Textures and soundscapes Granular synthesis, LPC, stochastic and wavelet-based methods TransientsOnset detection, physical models, granular synthesis, sines+transients+noise models