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Ananya Misra, Perry Cook Princeton University

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

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Ananya Misra, Perry Cook Princeton University

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  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 wave Triangle wave Sawtooth 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 synthesis Gait modelingCook, 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 windchimes Baby 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) Time-frequency LPC;Athineos&Ellis, 2003 Noise-excited LPC

  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

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