Skip to main content

Simulating Naming Latency Effects

  • Conference paper
  • First Online:
Advances in Artificial Intelligence (Canadian AI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9091))

Included in the following conference series:

  • 2637 Accesses

Abstract

Pronunciation by analogy (PbA) is a data-driven method for converting letters to sound, with potential application to text-to-speech systems. We studied the capability of PbA to account for a broad range of naming latency phenomena in English. These phenomena included the lexicality, regularity, consistency, frequency, and length effects. To simulate these effects, various features of the PbA pronunciation lattice (a data structure that is produced for generating the pronunciation of a spelling pattern) were investigated. These measures included the number of arcs, nodes, pattern matchings and candidate pronunciations. While each of these individual features were able to replicate many of the effects, a measure of complexity that combined the frequency of the words as well as the number of candidates and arcs successfully simulated all of the effects tested.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

  1. Bagshaw, P.C.: Phonemic transcription by analogy in text-to-speech synthesis: Novel word pronunciation and lexicon compression. Computer Speech and Language 12(2), 119–142 (1998)

    Article  Google Scholar 

  2. Baron, J., Strawson, C.: Use of orthographic and word-specific knowledge in reading aloud. Journal of Experimental Psychology: Human Perception and Performance 2(3), 386–393 (1976)

    Google Scholar 

  3. Barton, J.J., Hanif, H.M., Eklinder Björnström, L., Hills, C.: The word-length effect in reading: A review. Cognitive Neuropsychology 31(5–6), 378–412 (2014)

    Article  Google Scholar 

  4. Bisani, M., Ney, H.: Joint-sequence models for grapheme-to-phoneme conversion. Speech Communication 50(5), 434–451 (2008)

    Article  Google Scholar 

  5. Coltheart, M.: Lexical access in simple reading tasks. In: Underwood, G. (ed.) Strategies of Information Processing, pp. 151–216. Academic Press, New York (1978)

    Google Scholar 

  6. Coltheart, M., Curtis, B., Atkins, P., Haller, M.: Models of reading aloud: Dual-route and parallel-distributed-processing approaches. Psychological Review 100(4), 589–608 (1993)

    Article  Google Scholar 

  7. Coltheart, M., Patterson, K.E., Marshall, J.C. (eds.): Deep Dyslexia. Routledge and Kegan Paul, London (1980)

    Google Scholar 

  8. Coltheart, M., Rastle, K., Perry, C., Langdon, R., Ziegler, J.: DRC: A dual-route cascaded model of visual word recognition and reading aloud. Psychological Review 108(1), 204–256 (2001)

    Article  Google Scholar 

  9. Daelemans, W., van den Bosch, A., Weijters, T.: IGTree: Using trees for compression and classification in lazy learning algorithms. Artificial Intelligence Review 11(1–5), 407–423 (1997)

    Article  Google Scholar 

  10. Damper, R.I., Marchand, Y., Adamson, M.J., Gustafson, K.: Evaluating the pronunciation component of text-to-speech systems for English: A performance comparison of different approaches. Computer Speech and Language 13(2), 155–176 (1999)

    Article  Google Scholar 

  11. Damper, R.I., Marchand, Y.: Information fusion approaches to the automatic pronunciation of print by analogy. Information Fusion 7(2), 207–220 (2006)

    Article  Google Scholar 

  12. Dedina, M.J., Nusbaum, H.C.: Pronounce: A program for pronunciation by analogy. Computer Speech and Language 5(1), 55–64 (1991)

    Article  Google Scholar 

  13. Eriksen, C.W., Pollak, M.D., Montague, W.E.: Implicit speech: mechanism in perceptual encoding. Journal of Experimental Psychology 84(3), 502–507 (1970)

    Article  Google Scholar 

  14. Forster, K.I., Chambers, S.M.: Lexical access and naming time. Journal of Verbal Learning and Verbal Behavior 12, 627–635 (1973)

    Article  Google Scholar 

  15. Frederiksen, J., Kroll, J.: Spelling and sound: Approaches to the internal lexicon. Journal of Experimental Psychology: Human Perception and Performance 2(3), 361–379 (1976)

    Google Scholar 

  16. Glushko, R.J.: The organization and activation of orthographic knowledge in reading aloud. Journal of Experimental Psychology: Human Perception and Performance 5(4), 674–691 (1979)

    Google Scholar 

  17. Humphreys, G.W., Evett, L.J.: Are there independent lexical and non-lexical routes in word processing? An evaluation of the dual route theory of reading. Behavioral and Brain Sciences 8(4), 689–739 (1985)

    Article  Google Scholar 

  18. Handbook of the International Phonetic Association: A Guide to the Use of the International Phonetic Alphabet. Cambridge University Press, Cambridge (1999)

    Google Scholar 

  19. Jared, D.: Spelling-sound consistency affects the naming of high-frequency words. Journal of Memory and Language 36, 505–529 (1997)

    Article  Google Scholar 

  20. Kučera, H., Francis, W.N.: Computational Analysis of Present-Day American English. Brown University Press, Providence (1967)

    Google Scholar 

  21. Marchand, Y., Damper, R.I.: A multistrategy approach to improving pronunciation by analogy. Computational Linguistics 26(2), 195–219 (2000)

    Article  Google Scholar 

  22. Mason, M.: From print to sound in mature readers as a function of reader ability and two forms of orthographic regularity. Memory & Cognition 6(5), 568–581 (1978)

    Article  Google Scholar 

  23. Parkin, A.J.: Phonological recoding in lexical decision: Effects of spelling-to-sound regularity depend on how regularity is defined. Memory and Cognition 10(1), 43–53 (1982)

    Article  Google Scholar 

  24. Patterson, K.E., Morton, J.: From orthography to phonology: An attempt at an old interpretation. In: Patterson, K.E., Marshall, J.C., Coltheart, M. (eds.) Surface Dyslexia: Neuropsychological and Cognitive Studies of Phonological Reading, pp. 335–359. Lawrence Erlbaum Associates, London (1985)

    Google Scholar 

  25. Perry, C., Ziegler, J.C., Zorzi, M.: Nested incremental modeling in the development of computational theories: the CDP+ model of reading aloud. Psychological Review 114(2), 273 (2007)

    Article  Google Scholar 

  26. Perry, C., Ziegler, J.C., Zorzi, M.: Beyond single syllables: Large-scale modeling of reading aloud with the connectionist dual process (CDP++) model. Cognitive Psychology 61(2), 106–151 (2010)

    Article  Google Scholar 

  27. Pirrelli, V., Yvon, F.: The hidden dimension: A paradigmatic view of data-driven NLP. Journal of Experimental and Theoretical Artificial Intelligence 11(3), 391–408 (1999)

    Article  Google Scholar 

  28. Plaut, D.C., McClelland, J.L., Seidenberg, M.S., Patterson, K.E.: Understanding normal and impaired word reading: Computational principles in quasi-regular domains. Psychological Review 103(1), 56–115 (1996)

    Article  Google Scholar 

  29. Pritchard, S.C., Coltheart, M., Palethorpe, S., Castles, A.: Nonword reading: comparing dual-route cascaded and connectionist dual-process models with human data. Journal of Experimental Psychology: Human Perception and Performance 38(5), 1268 (2012)

    Google Scholar 

  30. Rao, K., Peng, F., Sak, H., Beaufays, F.: Grapheme-to-phoneme conversion using long short-term memory recurrent neural networks. In: Proceedings of ICASSP (2015)

    Google Scholar 

  31. Sejnowski, T.J., Rosenberg, C.R.: Parallel networks that learn to pronounce English text. Complex Systems 1(1), 145–168 (1987)

    MATH  Google Scholar 

  32. Thorndike, E.L., Lorge, I.: The Teachers’ Word Book of 30,000 Words. Columbia University, NY, Teachers’ College (1944)

    Google Scholar 

  33. Venezky, R.L.: The Structure of English Orthography. Mouton, The Hague (1970)

    Google Scholar 

  34. Wijk, A.: Rules of Pronunciation of the English Language. Oxford University Press, Oxford (1966)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yannick Marchand .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Marchand, Y., Damper, R. (2015). Simulating Naming Latency Effects. In: Barbosa, D., Milios, E. (eds) Advances in Artificial Intelligence. Canadian AI 2015. Lecture Notes in Computer Science(), vol 9091. Springer, Cham. https://doi.org/10.1007/978-3-319-18356-5_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-18356-5_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18355-8

  • Online ISBN: 978-3-319-18356-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics