Interference effects of phonological similarity in word production arise from competitive incremental learning

Qingqing Qu*, Chen Feng*, Markus F Damian

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

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In the blocked cyclic naming task, native Mandarin speakers named pictures with disyllabic names in small sets and blocks, with the critical manipulation whether pictures within a block shared an atonal syllable or not. We found the expected facilitation when the overlapping portion of responses was in word-initial position, but we also replicated a recent observation that with ‘inconsistent’ overlap (shared syllables could be either in first or second word position), form overlap causes interference. Crucially, interference also occurred when phonologically unrelated filler trials or trials which required a nonlinguistic response were interleaved with the critical pictures. The same pattern was found with written responses and orthographic radical overlap. The results are best explained via “competitive incremental learning” between lexical and phonological representations. A computer simulation confirms that this principle generates interference, and that the result is unaffected by filler trials. We conclude that incremental learning constitutes a universal principle in the mapping from semantics to phonology in language production.
Original languageEnglish
Article number104738
Number of pages17
Early online date22 Apr 2021
Publication statusPublished - 1 Jul 2021

Bibliographical note

Funding Information:
This work was supported by the National Natural Science Foundation of China (No. 31771212 and No. 62061136001 ), Youth Innovation Promotion Association ( Chinese Academy of Sciences ), and Youth Talent Project ( China Association for Science and Technology ) to Qingqing Qu. We thank Polly Barr for helpful comments on this manuscript.

Publisher Copyright:
© 2021 Elsevier B.V.


  • word production
  • speaking
  • writing
  • Chinese
  • incremental learning


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