Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

The remarkable inefficiency of word recognition

Nature volume 423, pages 752–756 (2003)Cite this article

Abstract

Do we recognize common objects by parts, or as wholes? Holistic recognition would be efficient, yet people detect a grating of light and dark stripes by parts. Thus efficiency falls as the number of stripes increases, in inverse proportion, as explained by probability summation among independent feature detectors1. It is inefficient to detect correlated components independently. But gratings are uncommon artificial stimuli that may fail to tap the full power of visual object recognition. Familiar objects become special as people become expert at judging them2,3, possibly because the processing becomes more holistic. Letters and words were designed to be easily recognized, and, through a lifetime of reading, our visual system presumably has adapted to do this as well as it possibly can. Here we show that in identifying familiar English words, even the five most common three-letter words, observers have the handicap predicted by recognition by parts: a word is unreadable unless its letters are separately identifiable. Efficiency is inversely proportional to word length, independent of how many possible words (5, 26 or thousands) the test word is drawn from. Human performance never exceeds that attainable by strictly letter- or feature-based models. Thus, everything seen is a pattern of features. Despite our virtuosity at recognizing patterns and our expertise from reading a billion letters, we never learn to see a word as a feature; our efficiency is limited by the bottleneck of having to rigorously and independently detect simple features.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: By letter or by word? a, Both lines of the quotation have the same total contrast energy.
Figure 2: The effect of word length.
Figure 3: Proportion correct in identifying a letter (filled symbols) or a 5-letter word (open symbols) in noise as a function of contrast.
Figure 4: The word superiority effect.

Similar content being viewed by others

References

  1. Robson, J. G. & Graham, N. Probability summation and regional variation in contrast sensitivity across the visual field. Vision Res. 21, 409–418 (1981)

    Article  CAS  Google Scholar 

  2. Diamond, R. & Carey, S. Why faces are and are not special: an effect of expertise. J. Exp. Psychol. Gen. 115, 107–117 (1986)

    Article  CAS  Google Scholar 

  3. Gauthier, I., Skudlarski, P., Gore, J. C. & Anderson, A. W. Expertise for cars and birds recruits brain areas involved in face recognition. Nature Neurosci. 3, 191–197 (2000)

    Article  CAS  Google Scholar 

  4. Treisman, A. & Schmidt, H. Illusory conjunctions in the perception of objects. Cogn. Psychol. 14, 107–141 (1982)

    Article  CAS  Google Scholar 

  5. Biederman, I. Recognition-by-components: a theory of human image understanding. Psychol. Rev. 94, 115–147 (1987)

    Article  Google Scholar 

  6. Tarr, M. J. & Buelthoff, H. H. Image-based object recognition in man, monkey and machine. Cognition 67, 1–20 (1998)

    Article  CAS  Google Scholar 

  7. Pelli, D. G., Palomares, M. & Majaj, N. J. Crowding is unlike ordinary masking: distinguishing feature detection and integration. J. Vision [online] 〈http://www.journalofvision.org/〉 (in the press)

  8. Cattell, J. M. The time taken up by cerebral operations. Mind 11, 220–242 (1886)

    Article  Google Scholar 

  9. Huey, E. B. The Psychology and Pedagogy of Reading (Macmillan, New York, 1908)

    Google Scholar 

  10. Reicher, G. M. Perceptual recognition as a function of the meaningfulness of stimulus material. J. Exp. Psychol. 81, 275–280 (1969)

    Article  CAS  Google Scholar 

  11. Wheeler, D. D. Processes in word recognition. Cogn. Psychol. 1, 59–85 (1970)

    Article  Google Scholar 

  12. Johnston, J. C. & McClelland, J. L. Perception of letters in words: seek not and ye shall find. Science 184, 1192–1194 (1974)

    Article  ADS  CAS  Google Scholar 

  13. Johnston, J. C. & McClelland, J. L. Experimental tests of a hierarchical model of word identification. J. Verbal Learn. Verbal Behav. 19, 503–524 (1980)

    Article  Google Scholar 

  14. McClelland, J. L. & Rumelhart, D. E. An interactive activation model of context effects in letter perception: Part 1. An account of basic findings. Psychol. Rev. 88, 375–407 (1981)

    Article  Google Scholar 

  15. Prinzmetal, W. & Silvers, B. The word without the tachistoscope. Percept. Psychophys. 55, 296–312 (1994)

    Article  CAS  Google Scholar 

  16. Jordan, T. R. & Bevan, K. M. Position-specific masking and the word–letter phenomenon: reexamining the evidence from the Reicher-Wheeler paradigm. J. Exp. Psychol. Hum. Percept. Perform. 22, 1416–1433 (1996)

    Article  Google Scholar 

  17. Peterson, W. W., Birdsall, T. G. & Fox, W. C. Theory of signal detectability. IRE Trans. Inf. Theory 4, 171–212 (1954)

    Article  Google Scholar 

  18. Pelli, D. G. & Farell, B. Why use noise? J. Opt. Soc. Am. A 16, 647–653 (1999)

    Article  ADS  CAS  Google Scholar 

  19. Tanner, W. P. Jr & Birdsall, T. G. Definitions of d′ and η as psychophysical measures. J. Acoust. Soc. Am. 30, 922–928 (1958)

    Article  ADS  Google Scholar 

  20. Legge, G. E., Pelli, D. G., Rubin, G. S. & Schleske, M. M. Psychophysics of reading—I. Normal vision. Vision Res. 25, 239–252 (1985)

    Article  CAS  Google Scholar 

  21. Pelli, D. G., Burns, C. W., Farell, B. & Moore, D. C. Identifying letters. Vision Res. (in the press)

  22. Campbell, F. W. & Robson, J. G. Application of Fourier analysis to the visibility of gratings. J. Physiol. (Lond.) 197, 551–566 (1968)

    Article  CAS  Google Scholar 

  23. Watson, A. B. & Robson, J. G. Discrimination at threshold: labelled detectors in human vision. Vision Res. 21, 1115–1122 (1981)

    Article  CAS  Google Scholar 

  24. Kucera, H. & Francis, W. N. Computational Analysis of Present-Day American English (Brown Univ. Press, Providence, 1967)

    Google Scholar 

  25. Hadley, J. A. & Healy, A. F. When are reading units larger than the letter? Refinement of the Unitization Reading Model. J. Exp. Psychol. Learn. Mem. Cogn. 17, 1062–1073 (1991)

    Article  Google Scholar 

  26. Barlow, H. B. Summation and inhibition in the frog's retina. J. Physiol. (Lond.) 119, 69–88 (1953)

    Article  CAS  Google Scholar 

  27. Solomon, J. A. & Pelli, D. G. The visual filter mediating letter identification. Nature 369, 395–397 (1994)

    Article  ADS  CAS  Google Scholar 

  28. Majaj, N. J., Liang, Y. X., Martelli, M., Berger, T. D. & Pelli, D. G. The channel for reading. J. Vision [online] 3 〈http://www.journalofvision.org/〉 (2003)

  29. Selfridge, O. Pandemonium: a paradigm for learning. Symposium on the Mechanization of Thought Processes 513–526 (HM Stationery Office, London, 1959)

    Google Scholar 

  30. Johnston, J. C. A test of the sophisticated guessing theory of word perception. Cogn. Psychol. 10, 123–153 (1978)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

Thanks to our many friends and colleagues who provided helpful comments, especially W. S. Geisler and R. F. Murray, who suggested that psychometric steepness may help to explain the reciprocal relation between efficiency and word length, J. M. Radner, who helped us say what we meant, I. Gauthier, D. J. Heeger, J. C. Johnston, M. S. Landy, G. E. Legge, J. M. Loomis, G. L. Murphy, R. E. Nixon, W. P. Prinzmetal and E. E. Smith. This work was supported by National Eye Institute grants to D.G.P. and B.F. D.C.M. was a Syracuse University undergraduate when she ran these experiments.

Author information

Authors and Affiliations

  1. Psychology and Neural Science, New York University, New York, New York, 10003, USA

    Denis G. Pelli

  2. Institute for Sensory Research, Syracuse University, Syracuse, New York, 13244-5290, USA

    Bart Farell & Deborah C. Moore

Authors
  1. Denis G. Pelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bart Farell
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Deborah C. Moore
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Denis G. Pelli.

Ethics declarations

Competing interests

The authors declare that they have no competing financial interests.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pelli, D., Farell, B. & Moore, D. The remarkable inefficiency of word recognition. Nature 423, 752–756 (2003). https://doi.org/10.1038/nature01516

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature01516

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing