Hostname: page-component-76fb5796d-vfjqv Total loading time: 0 Render date: 2024-04-29T10:38:06.525Z Has data issue: false hasContentIssue false
  • English
  • Français

The origins of duality of patterning in artificial whistled languages

Published online by Cambridge University Press:  11 March 2014

Tessa Verhoef
Tessa Verhoef*
Affiliation:
University of Amsterdam, 1012 VT Amsterdam, The Netherlands. E-mail: t.verhoef@uva.nl
Get access Rights & Permissions [Opens in a new window]

Abstract

In human speech, a finite set of basic sounds is combined into a (potentially) unlimited set of well-formed morphemes. Hockett (1960) placed this phenomenon under the term ‘duality of patterning’ and included it as one of the basic design features of human language. Of the thirteen basic design features Hockett proposed, duality of patterning is the least studied and it is still unclear how it evolved in language. Recent work shedding light on this is summarized in this paper and experimental data is presented. This data shows that combinatorial structure can emerge in an artificial whistled language through cultural transmission as an adaptation to human cognitive biases and learning. In this work the method of experimental iterated learning (Kirby et al. 2008) is used, in which a participant is trained on the reproductions of the utterances the previous participant learned. Participants learn and recall a system of sounds that are produced with a slide whistle. Transmission from participant to participant causes the whistle systems to change and become more learnable and more structured. These findings follow from qualitative observations, quantitative measures and a follow-up experiment that tests how well participants can learn the emerged whistled languages by generalizing from a few examples.

Keywords

cultural evolutioncombinatorial structurelanguage evolutionphonology
Type
Research Article
Information
Language and Cognition , Volume 4 , Special Issue 4: New perspectives on duality of patterning , December 2012 , pp. 357 - 380
Copyright
Copyright © UK Cognitive Linguistics Association 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abler, W. L. 1989. On the particulate principle of self-diversifying systems. Journal of Social and Biological Structures 12(1). 1–13.Google Scholar
Ackerman, F., Blevins, J. P. & Malouf, R.. 2009. Parts and wholes: Patterns of relatedness in complex morphological systems and why they matter. In Blevins, J. P. & Blevins, J. (eds.), Analogy in grammar: Form and acquisition, 54–82. Oxford: Oxford University Press.Google Scholar
Boersma, P. 2001. Praat, a system for doing phonetics by computer. Glot International 5(9/10). 341–345.Google Scholar
Browman, C. P. & Goldstein, L.. 1986. Towards an articulatory phonology. Phonology Yearbook 3. 219–252.Google Scholar
Clements, G. N. 2003. Feature economy in sound systems. Phonology 20. 287–333.Google Scholar
Christiansen, M. H. & Chater, N.. 2008. Language as shaped by the brain. Behavioral and Brain Sciences 31(5). 489–509.Google Scholar
Deacon, T. W. 1997. The symbolic species: The co-evolution of language and the brain. New York: WW Norton & Co.Google Scholar
de Boer, B. 2000. Self-organization in vowel systems. Journal of Phonetics 28(4). 441–465.Google Scholar
del Giudice, A. 2012. The emergence of duality of patterning through iterated learning. Language and cognition. [This volume].Google Scholar
del Giudice, A., Kirby, S. & Padden, C.. 2010. Recreating duality of patterning in the laboratory: a new experimental paradigm for studying emergence of sublexical structure. In Smith, A. D. M., Schouwstra, M., de Boer, B. & Smith, K. (eds.), The evolution of language: Proceedings of the 8th international conference, 399–400. Hackensack, NJ: World Scientific Press.Google Scholar
Doupe, A. J. & Kuhl, P. K.. 1999. Birdsong and human speech: Common themes and mechanisms. Annual Review of Neuroscience 22. 567–631.CrossRefGoogle ScholarPubMed
Dowman, M., Xu, J. & Griffiths, T. L.. 2008. A human model of color term evolution. In Smith, A. D. M., Smith, K. & Cancho, R. F. i (eds.), The evolution of language: Proceedings of the 7th international conference, 421–422. Hackensack, NJ: World Scientific Press.Google Scholar
Duda, R. O., Hart, P. E. & Stork, D. G.. 2001. Pattern recognition. New York: A Wiley-Interscience.Google Scholar
Galantucci, B. 2005. An experimental study of the emergence of human communication. Cognitive Science 29. 737–767.Google Scholar
Galantucci, B., Fowler, C. A. & Turvey, M. T.. 2006. The motor theory of speech perception reviewed. PsychonomicBulletin & Review 13(3). 361–377.CrossRefGoogle ScholarPubMed
Galantucci, B., Kroos, C. & Rhodes, T.. 2010. The effects of rapidity of fading on communication systems. Interaction Studies 11. 100–111.Google Scholar
Garrod, S., Fay, N., Lee, J., Oberlander, J. & MacLeod, T.. 2007. Foundations of representation: Where might graphical symbol systems come from? Cognitive Science 31. 961–987.Google Scholar
Griffiths, T., Kalish, M. & Lewandowsky, S.. 2008. Theoretical and empirical evidence for the impact of inductive biases on cultural evolution. Philosophical Transactions of the Royal Society: Biological Sciences 363(1509). 3503–3514.Google Scholar
Hauser, M., Newport, E. & Aslin, R.. 2001. Segmentation of the speech stream in a non-human primate: Statistical learning in cotton-top tamarins. Cognition 78(3). B53–B64.CrossRefGoogle Scholar
Hockett, C. 1960. The origin of speech. Scientific American 203. 88–96.CrossRefGoogle ScholarPubMed
Hockett, C. F. & Altmann, S.. 1968. A note on design features. In Sebeok, T. A. (ed.), Animal communication; Techniques of study and results of research, 61–72. Bloomington: Indiana University Press.Google Scholar
Israel, A. & Sandler, W.. 2011. Phonological category resolution in a new sign language: A comparative study of handshapes. In Channon, R. & van der Hulst, H. (eds.), Formational units in sign languages, 177–202. Berlin: Mouton de Gruyter.Google Scholar
Keogh, E. J. & Pazzani, M. J.. 2001. Derivative dynamic time warping. First SIAM International Conference on Data Mining (sdm2001). 1–11.Google Scholar
Kirby, S., Cornish, H. & Smith, K.. 2008. Cumulative cultural evolution in the laboratory: An experimental approach to the origins of structure in human language. Proceedings of the National Academy of Sciences 105(31). 10681–10686.Google Scholar
Kirby, S. & Hurford, J.. 2002. The emergence of linguistic structure: An overview of the iterated learning model. In Cangelosi, A. & Parisi, D. (eds.), Simulating the evolution of language, 121–148. New York: Springer Verlag.Google Scholar
Kluender, K. R., Diehl, R. L. & Killeen, P. R.. 1987. Japanese quail can learn phonetic categories. Science 237(4819). 1195–1197.Google Scholar
Massaro, D. W. & Chen, T. H.. 2008. The motor theory of speech perception revisited. Psychonomic Bulletin and Review 15(2). 453–457.Google Scholar
Nowak, M., Krakauer, D. & Dress, A.. 1999. An error limit for the evolution of language. Proceedings of the Royal Society of London 266. 2131–2136.Google Scholar
Ohala, J. J. 1980. Moderator's introduction to symposium on phonetic universals in phonological systems and their explanation. Proceedings of the 9th International Congress of Phonetic Sciences. 181–185.Google Scholar
Page, E. B. 1963. Ordered hypotheses for multiple treatments: A significance test for linear ranks. Journal of the American Statistical Association 58(301). 216–230.CrossRefGoogle Scholar
Payne, R.S. & McVay, S.. 1971. Songs of humpack whales. Science 173(3997). 585–597.Google Scholar
Sakoe, H. & Chiba, S.. 2003. Dynamic programming algorithm optimization for spoken word recognition. Acoustics, Speech and Signal Processing, IEEE Transactions on 26(1). 43–49.Google Scholar
Sandler, W., Aronoff, M., Meir, I. & Padden, C.. 2011. The gradual emergence of phonological form in a new language. Natural Language and Linguistic Theory. 29(2). 503–543.Google Scholar
Scott-Phillips, T. C. & Kirby, S.. 2010. Language evolution in the laboratory. Trends in cognitive sciences 14. 411–417.Google Scholar
Scott-Phillips, T. C., Kirby, S. & Ritchie, G. R. S.. 2009. Signalling signalhood and the emergence of communication. Cognition 113(2). 226–233.Google Scholar
Shannon, C. E. 1948. A mathematical theory of communication. Bell System Technical Journal 27. 379–423, 623–656.Google Scholar
Smith, K., Kirby, S. & Brighton, H.. 2003. Iterated learning: A framework for the emergence of language. Artificial Life 9(4). 371–386.Google Scholar
Smith, K., Smith, A. D. M. & Blythe, R. A.. 2011. Cross-situational learning: An experimental study of word-learning mechanisms. Cognitive Science 35. 480–498.Google Scholar
Smith, K. & Wonnacott, E.. 2010. Eliminating unpredictable variation through iterated learning. Cognition 116. 444–449.Google Scholar
Steels, L. 1997. The synthetic modeling of language origins. Evolution of Communication 1(1). 1–34.Google Scholar
Verhoef, T. & de Boer, B.. 2011. Cultural emergence of feature economy in an artificial whistled language. In Zee, E. & Lee, W. (eds.), Proceedings of the 17th international congress of phonetic sciences, 2066–2069. Hong Kong: City University of Hong Kong.Google Scholar
Verhoef, T., de Boer, B. & Kirby, S.. 2012. Holistic or synthetic protolanguage: Evidence from iterated learning of whistled signals. In Scott-Phillips, T. C., Tamariz, M., Cartmill, E. A. & Hurford, J. R. (eds.), The evolution of language: Proceedings of the 9th international conference (evolang9), 368–375. Hackensack, NJ: World Scientific.Google Scholar
Verhoef, T., Kirby, S. & Padden, C.. 2011. Cultural emergence of combinatorial structure in an artificial whistled language. In Carlson, L., Hölscher, C. & Shipley, T. (eds.), Proceedings of the 33rd annual conference of the cognitive science society, 483–488. Austin, TX: Cognitive Science Society.Google Scholar
Williams, H. & Nottebohm, F.. 1985. Auditory responses in avian vocal motor neurons: A motor theory for song perception in birds. Science 229(4710). 279–282.Google Scholar
Zuidema, W. & de Boer, B.. 2009. The evolution of combinatorial phonology. Journal of Phonetics 37(2). 125–144.Google Scholar