Skip to main content
SpringerLink
Log in

Convergence Synthesis of Dynamic Frequency Modulation Tones Using an Evolution Strategy

  • Conference paper
Applications of Evolutionary Computing (EvoWorkshops 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3449))

Included in the following conference series:

Abstract

This paper reports on steps that have been taken to enhance previously presented evolutionary sound matching work. In doing so, the convergence characteristics are shown to provide a synthesis method that produces interesting sounds. The method implements an Evolution Strategy to optimise a set of real-valued Frequency Modulation parameters. The development of the evolution is synthesised as optimisation takes place, and the corresponding dynamic sound can be observed developing from initial disorder, into a stable, static tone.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Horner, A.: Spectral Matching of Musical Instrument Tones, PhD dissertation, University of Illinois Computer Science Department, Report No. UIUCDCS-R-93-1805 UILU-ENG-93-1720 (1993)

    Google Scholar 

  2. Horner, A.: Nested Modulator and Feedback FM Matching of Instrument Tones. IEEE Transactions on Speech and Audio Processing 6(6), 398–409 (1998)

    Article  Google Scholar 

  3. Wavetable Matching Synthesis of Dynamic Instruments, Audio Engineering Society Preprint No. 4389, pp. 1–23 (1996); Presented at the 101st Audio Engineering Society Convention

    Google Scholar 

  4. Cheung, N.-M., Horner, A.: Group Synthesis with Genetic Algorithms. Journal of the Audio Engineering Society 44(3), 130–147 (1996); Abstract on JAES Homepage

    Google Scholar 

  5. Wehn, K.: Using Ideas from Natural Selection to Evolve Synthesized Sounds. In: Proc. Digital Audio Effects (DAFX 1998), Barcelona (1998)

    Google Scholar 

  6. Garcia, R.: Growing Sound Synthesizers using Evolutionary Methods. In: European Conference in Artificial Life ECAL 2001. Artificial Life Models for Musical Applications, University of Economics, Prague, Czech Republic (2001)

    Google Scholar 

  7. Manzolli, J., Maia, A., Fornari, J., Damiani, F.: The evolutionary sound synthesis method. In: Proceedings of the ninth ACM international conference on Multimedia, Ottawa, Canada (2001)

    Google Scholar 

  8. Chowning, J.: The synthesis of complex audio spectra by means of frequency modulation. Journal of the Audio Engineering Society 21, 526–534 (1973)

    Google Scholar 

  9. Beyer, H., Schwefel, H.: Evolution Strategies: A Comprehensive Introduction. Natural Computing: an international journal 1(1), 3–52 (2002)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Computing, Engineering & Mathematical Sciences, The University of the West of England, Frenchay, Bristol, BS16 1QY, UK

    Thomas J. Mitchell & Anthony G. Pipe

Authors
  1. Thomas J. Mitchell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anthony G. Pipe
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Johannes Gutenberg University, Mainz, Germany

    Franz Rothlauf

  2. Institute AIFB, University of Karlsruhe, 76128, Karlsruhe, Germany

    Jürgen Branke

  3. Dipartimento di Ingegneria dell’Informazione, Università di Parma,  

    Stefano Cagnoni

  4. School of Mathematical and Computer Science, Heriot-Watt University, EH14 8AS, Edinburgh, UK

    David Wolfe Corne

  5. Institute of Computer Science, University of Bremen, 28359, Bremen, Germany

    Rolf Drechsler

  6. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

  7. CISUC, Department of Informatics Engineering, University of Coimbra, Polo II of the University of Coimbra, 3030, Coimbra, Portugal

    Penousal Machado

  8. ICIS, Radboud University Nijmegen, The Netherlands

    Elena Marchiori

  9. Universidade de A Coruña, CP 15071, A Coruña, Spain

    Juan Romero

  10. School of Computing Sciences, University of East Anglia, UEA Norwich, NR4 7TJ, Norwich, UK

    George D. Smith

  11. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mitchell, T.J., Pipe, A.G. (2005). Convergence Synthesis of Dynamic Frequency Modulation Tones Using an Evolution Strategy. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2005. Lecture Notes in Computer Science, vol 3449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32003-6_54

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-32003-6_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25396-9

  • Online ISBN: 978-3-540-32003-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation