Psychonomic Bulletin & Review

, Volume 16, Issue 3, pp 486–490 | Cite as

Statistical learning of adjacent and nonadjacent dependencies among nonlinguistic sounds

  • Andrea L. Gebhart
  • Elissa L. Newport
  • Richard N. Aslin
Brief Reports


Previous work has demonstrated that adults are capable of learning patterned relationships among adjacent syllables or tones in continuous sequences but not among nonadjacent syllables. However, adults are capable of learning patterned relationships among nonadjacent elements (segments or tones) if those elements are perceptually similar. The present study significantly broadens the scope of this previous work by demonstrating that adults are capable of encoding the same types of structure among unfamiliar nonlinguistic and nonmusical elements but only after much more extensive exposure. We presented participants with continuous streams of nonlinguistic noises and tested their ability to recognize patterned relationships. Participants learned the patterns among noises within adjacent groups but not within nonadjacent groups unless a perceptual similarity cue was added. This result provides evidence both that statistical learning mechanisms empower adults to extract structure from nonlinguistic and nonmusical elements and that perceptual similarity eases constraints on nonadjacent pattern learning. Supplemental materials for this article can be downloaded from


Statistical Learning Perceptual Similarity Transitional Probability Speech Stream Triplet Boundary 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material (237 kb)
Supplementary material, approximately 340 KB.


  1. Aslin, R. N., Saffran, J. R., & Newport, E. L. (1998). Computation of conditional probability statistics by human infants. Psychological Science, 9, 321–324.CrossRefGoogle Scholar
  2. Chomsky, N. A. (1957). Syntactic structures. The Hague: Mouton.Google Scholar
  3. Cleeremans, A., & McClelland, J. L. (1991). Learning the structure of event sequences. Journal of Experimental Psychology: General, 120, 235–253.CrossRefGoogle Scholar
  4. Creel, S. C., Newport, E. L., & Aslin, R. N. (2004). Distant melodies: Statistical learning of nonadjacent dependencies in tone sequences. Journal of Experimental Psychology: Learning, Memory, & Cognition, 30, 1119–1130.CrossRefGoogle Scholar
  5. Endress, A. D., & Mehler, J. (2009). The surprising power of statistical learning: When fragment knowledge leads to false memories of unheard words. Journal of Memory & Language, 60, 351–367.CrossRefGoogle Scholar
  6. Fiser, J., & Aslin, R. N. (2002). Statistical learning of higher-order temporal structure from visual shape sequences. Journal of Experimental Psychology: Learning, Memory, & Cognition, 28, 458–467.CrossRefGoogle Scholar
  7. Gómez, R. L. (2002). Variability and detection of invariant structure. Psychological Science, 13, 431–436.CrossRefPubMedGoogle Scholar
  8. Hauser, M. D., Newport, E. L., & Aslin, R. N. (2001). Segmentation of the speech stream in a non-human primate: Statistical learning in cotton-top tamarins. Cognition, 78, B53-B64.CrossRefPubMedGoogle Scholar
  9. Johnson, S. P., Fernandes, K. J., Frank, M. C., Kirkham, N. Z., Marcus, G. F., Rabagliati, H., & Slemmer, J. A. (2009). Abstract rule learning for visual sequences in 8- and 11-month-olds. Infancy, 14, 2–18.CrossRefPubMedGoogle Scholar
  10. Kirkham, N. Z., Slemmer, J. A., & Johnson, S. P. (2002). Visual statistical learning in infancy: Evidence for a domain general learning mechanism. Cognition, 83, B35-B42.CrossRefPubMedGoogle Scholar
  11. Marcus, G. F., Fernandes, K. J., & Johnson, S. P. (2007). Infant rule learning facilitated by speech. Psychological Science, 18, 387–391.CrossRefPubMedGoogle Scholar
  12. Newport, E. L., & Aslin, R. N. (2004). Learning at a distance: I. Statistical learning of non-adjacent dependencies. Cognitive Psychology, 48, 127–162.CrossRefPubMedGoogle Scholar
  13. Onnis, L., Monaghan, P., Richmond, K., & Chater, N. (2005). Phonology impacts segmentation in online speech processing. Journal of Memory & Language, 53, 225–237.CrossRefGoogle Scholar
  14. Peña, M., Bonatti, L. L., Nespor, M., & Mehler, J. (2002). Signaldriven computations in speech processing. Science, 298, 604–607.CrossRefPubMedGoogle Scholar
  15. Perruchet, P., & Pacton, S. (2006). Implicit learning and statistical learning: One phenomenon, two approaches. Trends in Cognitive Sciences, 10, 233–238.CrossRefPubMedGoogle Scholar
  16. Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274, 1926–1928.CrossRefPubMedGoogle Scholar
  17. Saffran, J. R., Johnson, E. K., Aslin, R. N., & Newport, E. L. (1999). Statistical learning of tone sequences by adults and infants. Cognition, 70, 27–52.CrossRefPubMedGoogle Scholar
  18. Saffran, J. R., Newport, E. L., & Aslin, R. N. (1996). Word segmentation: The role of distributional cues. Journal of Memory & Language, 35, 606–621.CrossRefGoogle Scholar
  19. Saffran, J. R., Newport, E. L., Aslin, R. N., Tunick, R. A., & Barrueco, S. (1997). Incidental language learning: Listening (and learning) out of the corner of your ear. Psychological Science, 8, 101–105.CrossRefGoogle Scholar
  20. Saffran, J. R., Pollak, S. D., Seibel, R. L., & Shkolnik, A. (2007). Dog is a dog is a dog: Infant rule learning is not specific to language. Cognition, 105, 669–680.CrossRefPubMedGoogle Scholar
  21. Toro, J. M., & Trobalón, J. B. (2005). Statistical computations over a speech stream in a rodent. Perception & Psychophysics, 67, 867–875.CrossRefGoogle Scholar

Copyright information

© The Psychonomic Society, Inc 2009

Authors and Affiliations

  • Andrea L. Gebhart
    • 1
  • Elissa L. Newport
    • 1
  • Richard N. Aslin
    • 1
  1. 1.Department of Brain and Cognitive SciencesUniversity of RochesterRochesterNY

Personalised recommendations