Skip to main content
SpringerLink
Log in

Digital Signal Analysis, Editing, and Synthesis

  • Chapter
Book cover Animal Acoustic Communication

Abstract

Historically, the quantitative study of sound has been wedded to the development of sound-measurement technology. Researchers have routinely seized on and resourcefully adapted various technological tools, whether intended for sound analysis or not. Sabine (1900), for example, developed acoustical reverberation theory in an empty theater at Harvard University, using an organ pipe, a chronograph, and his own hearing to measure reverberant sound duration. Similarly, Brand (1934) characterized the time-varying frequency of birdsong by recording vocalizations on motion-picture film and measuring spatial line-density on the soundtrack. Successive milestones in sound-measurement technology — notably the microphone, the oscilloscope, and later the sound spectrograph — helped researchers to visualize and measure sounds but not to model them directly. Modeling of acoustic communication was instead typically performed indirectly via statistical analysis, comparison, and classification of individual measured sound features.

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 139.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
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

  • Beecher MD (1988) Spectrographic analysis of animal vocalizations: implications of the “uncertainty” principle. Bioacoustics 1:187–208

    Google Scholar 

  • Beeman K (1987) SIGNAL V2.5 User’s Guide [DEC PDP]. Engineering Design, Belmont, Massachusetts

    Google Scholar 

  • Beeman K (1989) SIGNAL V1.3 User’s Guide [IBM PC]. Engineering Design, Belmont, Massachusetts

    Google Scholar 

  • Beeman K (1991) RTS V1.0 User’s Guide [IBM PC]. Engineering Design, Belmont, Massachusetts

    Google Scholar 

  • Beeman K (1996a) RTS V2.0 User’s Guide [IBM PC]. Engineering Design, Belmont, Massachusetts

    Google Scholar 

  • Beeman K (1996b) SIGNAL V3.0 User’s Guide [IBM PC]. Engineering Design, Belmont, Massachusetts

    Google Scholar 

  • Borror DJ (1965) Song variation in Maine song sparrows. Wilson Bull 77:5–37

    Google Scholar 

  • Brand AR (1934) A method for the intensive study of bird song. Auk 52:40–52

    Google Scholar 

  • Buck JR, Tyack PL (1993) A quantitative measure of similarity forTursiops truncatus signature whistles. J Acoust Soc Am 94:2497–2506

    Article  PubMed  CAS  Google Scholar 

  • Charif RA, Mitchell S, Clark CW (1995) CANARY 1.2 users manual. Cornell Laboratory of Ornithology, Ithaca New York

    Google Scholar 

  • Clark CW (1982) The acoustic repertoire of the southern right whale, a quantitative analysis. Anim Behav 30:1060–1071

    Article  Google Scholar 

  • Clark CW, Marler P, Beeman K (1987) Quantitative analysis of animal vocal phonology: an application to swamp sparrow song. Ethology 76:101–115

    Article  Google Scholar 

  • Dabelsteen T, Pedersen SB (1985) A method for computerized modification of certain natural animal sounds for communication study purposes. Biol Cybern 52:399–404

    Article  PubMed  CAS  Google Scholar 

  • Dorrscheidt GJ (1978) A reversible method for sound analysis adapted to bio-acoustical experiments. Int J Bio Med Comput 9:127–145

    Article  CAS  Google Scholar 

  • Flanagan JL (1972) Speech analysis, synthesis, and perception, 2nd edn. Springer Berlin Heidelberg New York

    Google Scholar 

  • Gerhardt HC (1989) Acoustic pattern recognition in anuran amphibians. In: Dooling RJ, Hulse SH (eds) Comparative psychology of audition: Perceiving complex sounds. Erlbaum Assoc, Hillsdale, New Jersey, p 175

    Google Scholar 

  • Gerhardt HC (1992) Multiple messages in acoustic signals. Sem Neurosci 4:39–400

    Article  Google Scholar 

  • Greenewalt CH (1968) Bird Song: Acoustics and physiology. Smithsonian Institute Press, Washington, DC

    Google Scholar 

  • Hauser MD (1991) Sources of acoustic variation in rhesus macaque vocalizations. Ethology 89:29–46

    Article  Google Scholar 

  • Hauser MD (1992) Articulatory and social factors influence the acoustic structure of rhesus monkey vocalizations: a learned mode of production? J Acoust Soc Am 91:2175–2179

    Article  PubMed  CAS  Google Scholar 

  • Hauser MD, Schön Ybarra M (1994) The role of lip configuration in monkey vocalizations: experiments using Xylocaine as a nerve block. Brain Lang 46:232–244

    Article  PubMed  CAS  Google Scholar 

  • Hienz RD, Brady JV (1988) The acquisition of vowel discriminations by nonhuman primates. J Acoust Soc Am 84:186–194.

    Article  PubMed  CAS  Google Scholar 

  • Hopp SL, Sinnott JM, Owren MJ, Petersen MR (1992) Differential sensitivity of Japanese macaque (Macaca fuscata) and humans (Homo sapiens) to peak position along a synthetic coo call continuum. J Comp Physiol Psychol 106:128–136

    CAS  Google Scholar 

  • Klatt DH (1980) Software for a cascade/parallel formant synthesizer. J Acoust Soc Am 67:971–995

    Article  Google Scholar 

  • Koenig W, Dunn HK, Lacy LY (1946) The sound spectrograph. J Acoust Soc Am 18:19–49

    Article  Google Scholar 

  • Kroodsma DE (1974) Song learning, dialects and dispersal in Bewick’s wren. Z Tierpsychol 35:353–380

    Google Scholar 

  • Loughlin PJ, Atlas LE, Pitton JW (1993) Advanced time-frequency representations for speech processing. In: Cooke M, Beet S, Crawford M (eds) Visual representations of speech signals. Wiley, New York, p 27

    Google Scholar 

  • Margoliash D (1983) Song-specific neurons in the white-crowned sparrow. J Neurosci 3:1039–1048

    PubMed  CAS  Google Scholar 

  • Markel JD, Gray AH (1976) Linear prediction of speech. Springer, Berlin Heidelberg New York

    Book  Google Scholar 

  • Marier P, Pickert R (1984) Species-universal microstructure in the learned song of the swamp sparrow (Melospiza georgiana). Anim Behav 32:673–689

    Article  Google Scholar 

  • Martindale S (1980) A numerical approach to the analysis of solitary vireo songs. Condor 82:199–211

    Article  Google Scholar 

  • May B, Moody DB, Stebbins WC (1988) The significant features of Japanese macaque coo sounds: a psychophysical study. Anim Behav 36:1432–1444

    Article  Google Scholar 

  • Nelson DA (1992) Song overproduction and selective attrition lead to song sharing in the field sparrow (Spizella pusilla). Behav Ecol Sociobiol 30:415–424

    Article  Google Scholar 

  • Nelson DA, Croner LJ (1991) Song categories and their functions in the field sparrow (Spizella pusilla). Auk 108:42–52

    Google Scholar 

  • Nelson DA, Marier P, Palleroni A (1995) A comparative approach to vocal learning: intraspecific variation in the learning process. Anim Behav 50:83–97

    Article  Google Scholar 

  • Nowicki S, Capranica RR (1986) Bilateral syringeal interaction in vocal production of an oscine bird sound. Science 231:1297–1299

    Article  PubMed  CAS  Google Scholar 

  • Oppenheim AV, Schafer RW (1989) Discrete-time signal processing. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Owren MJ, Bernacki RH (1988) The acoustic features of vervet monkey alarm calls. J Acoust Soc Am 83:1927–1935

    Article  PubMed  CAS  Google Scholar 

  • Randall R (1977) Application of B&K equipment to frequency analysis. Brel & Kjr, Nrum, Denmark

    Google Scholar 

  • Richard JP (1991) Sound analysis and synthesis using an Amiga micro-computer. Bioacoustics 3:45–60

    Google Scholar 

  • Rosen S, Howell P (1991) Signals and systems for speech and hearing. Academic Press, New York

    Google Scholar 

  • Ryan MJ, Perrill SA, Wilczynski W (1992) Auditory tuning and call frequency predict population-based mating preferences in the cricket frog,Acris crepitans. Am Natural 139:1370–1383

    Article  Google Scholar 

  • Sabine WS (1900) Reverberation. In: Sabine WS (ed) Collected papers on acoustics. Dover, New York, P3

    Google Scholar 

  • Schafer RW (1975) Digital representation of speech signals. Proc IEEE 63:662–677

    Article  Google Scholar 

  • Sinnott JM (1989) Detection and discrimination of synthetic English vowels by old world monkeys (Cercopithecus, Macaca) and humans. J Acoust Soc Am 86:557–565

    Article  PubMed  CAS  Google Scholar 

  • Sparling DW, Williams JD (1978) Multivariate analysis of avian vocalizations. J Theor Biol 74:83–107

    Article  PubMed  CAS  Google Scholar 

  • Staddon JER, McGeorge LW, Bruce RA, Klein FF (1978) A simple method for the rapid analysis of animal sounds. Z Tierpsychol 48:306–330

    Google Scholar 

  • Stephen RO, Hartley JC (1995) Sound production in crickets. J Exp Biol 198:2139–2152

    PubMed  Google Scholar 

  • Stoddard PK (1990) Audio computers — theory of operation and guidelines for selection of systems and components. Bioacoustics 2:217–239

    Google Scholar 

  • Stremler FG (1977) Introduction to communication systems. Addison-Wesley, Reading, Massachusetts

    Google Scholar 

  • Suthers RA, Goller F, Hartley RS (1994) Motor dynamics of song production by mimic thrushes. J Neurobiol 25:917–936

    Article  PubMed  CAS  Google Scholar 

  • Wells MM, Henry CS (1992) Behavioral responses of green lacewings (Neuroptera: Chrysopidae) to synthetic mating songs. Anim Behav 44:641–652

    Article  Google Scholar 

  • Zoloth S, Dooling RJ, Miller R, Peters S (1980) A minicomputer system for the synthesis of animal vocalisations. Z Tierpsychol 54:151–162

    Google Scholar 

Download references

Authors
  1. K. Beeman
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dept. of Ecology and Evolutionary Biology, University of Arizona, 85721, Tucson, AZ, USA

    Steven L. Hopp

  2. Dept. of Psychology, Cornell University, 14853, Ithaca, NY, USA

    Michael J. Owren

  3. Dept of Psychology, Macquarie University, 2109, Sydney, NSW, Australia

    Christopher S. Evans

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Beeman, K. (1998). Digital Signal Analysis, Editing, and Synthesis. In: Hopp, S.L., Owren, M.J., Evans, C.S. (eds) Animal Acoustic Communication. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76220-8_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-76220-8_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-76222-2

  • Online ISBN: 978-3-642-76220-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation