Skip to main content

Part of the book series: Use R! ((USE R))

  • 3834 Accesses

Abstract

Variations of amplitude and frequency according to timeare commonly visualised through a time × frequency × amplitude density plot, named the spectrogram. The theory of the short-time discrete Fourier transform (and its inverse function), which is behind the spectrogram output, is introduced with a particular attention paid to the uncertainty principle. Practical solutions are given to display, tune, decorate, annotate, describe, animate, and print a 2D/3D spectrogram. The realization of a mean spectrum and a soundscape spectrum, which are computed on the short-time Fourier transform, is also introduced.

Audio files:synth-face.wavElliptorhina_chopardi.wavforest.wavtico.wavpeewit.wavsheep.wavorni.wav

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

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
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

Notes

  1. 1.

    http://www.mega-nerd.com/libsndfile/

  2. 2.

    http://www.fftw.org/

  3. 3.

    https://marce10.github.io/2016/12/12/Create_dynamic_spectro_in_R.html

  4. 4.

    https://ffmpeg.org/

References

  • Adler D, Murdoch D (2016) rgl: 3D visualization device system (OpenGL). http://CRAN.R-project.org/package=rgl, R package

  • Fristrup KM, Watkins WA (1992) Characterizing acoustic features of marine animal sounds. Tech. rep., Woods Hole Oceanographic Institution Technical Report WHOI-92-04

    Google Scholar 

  • Kasten EP, Gage SH, Fox J, Joo W (2012) The remote environmental assessment laboratory’s acoustic library: an archive for studying soundscape ecology. Eco Inform 12:50–67

    Google Scholar 

  • Katz J, Hafner SD, Donovan T (2016b) Tools for automated acoustic monitoring within the R package monitor. Bioacoustics 25:191–210

    Google Scholar 

  • Mallat S (2009) A wavelet tour of signal processing: the sparse way. Elsevier, Amsterdam

    Google Scholar 

  • Quatieri TF (2002) Discrete-time speech signal processing: principles and practice. Pearson, Noida

    Google Scholar 

  • Staszewski WJ, Robertson AN (2007) Time-frequency and time-scale analyses for structural health monitoring. Philos Trans R Soc A: Math Phys Eng Sci 365:449–477

    Article  MathSciNet  Google Scholar 

  • Sueur J, Aubin T (2006) When males whistle at females: complex fm signals in cockroaches. Naturwissenschaften 93:500–505

    Article  Google Scholar 

  • Welch PD (1967) The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoust 15:70–73

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Cite this chapter

Sueur, J. (2018). Spectrographic Visualization. In: Sound Analysis and Synthesis with R. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-77647-7_11

Download citation

Publish with us

Policies and ethics