Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2016 Sep 21:7:1345.
doi: 10.3389/fpsyg.2016.01345. eCollection 2016.

Fuzzy Nonnative Phonolexical Representations Lead to Fuzzy Form-to-Meaning Mappings

Affiliations
Free PMC article

Fuzzy Nonnative Phonolexical Representations Lead to Fuzzy Form-to-Meaning Mappings

Svetlana V Cook et al. Front Psychol. .
Free PMC article

Abstract

The present paper explores nonnative (L2) phonological encoding of lexical entries and dissociates the difficulties associated with L2 phonological and phonolexical encoding by focusing on similarly sounding L2 words that are not differentiated by difficult phonological contrasts. We test two main claims of the fuzzy lexicon hypothesis: (1) L2 fuzzy phonolexical representations are not fully specified and lack details at both phonological and phonolexical levels of representation (Experiment 1); and (2) fuzzy phonolexical representations can lead to establishing incorrect form-to-meaning mappings (Experiment 2). The Russian-English Translation Judgment Task (Experiment 1, TJT) explores how the degree of phonolexical similarity between a word and its lexical competitor affects lexical access of Russian words. Words with smaller phonolexical distance (e.g., parent-parrot) show longer reaction times and lower accuracy compared to words with a larger phonolexical distance (e.g., parent-parchment) in lower-proficiency nonnative speakers, and, to a lesser degree, higher-proficiency speakers. This points to a lack of detail in nonnative phonolexical representations necessary for efficient lexical access. The Russian Pseudo-Semantic Priming task (Experiment 2, PSP) addresses the vulnerability of form-to-meaning mappings as a consequence of fuzzy phonolexical representations in L2. We primed the target with a word semantically related to its phonological competitor, or a potentially confusable word. The findings of Experiment 2 extend the results of Experiment 1 that, unlike native speakers, nonnative speakers do not properly encode phonolexical information. As a result, they are prone to access an incorrect lexical representation of a competitor word, as indicated by a slowdown in the judgments to confusable words. The study provides evidence that fuzzy phonolexical representations result in unfaithful form-to-meaning mappings, which lead to retrieval of incorrect semantic content. The results of the study are in line with existing research in support of less detailed L2 phonolexical representations, and extend the findings to show that the fuzziness of phonolexical representations can arise even when confusable words are not differentiated by difficult phonological contrasts.

Keywords: Russian; form-to-meaning mapping; lexical access; nonnative auditory perception; phonological representations.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Mean RTs of match trials, non-competitor mismatch trials, and competitor mismatch trials of different Levenshtein distances for words of high and low frequency in Experiment 1 (TJT). Lines indicate linear regression lines of best fit for competitor mismatch targets of high and low frequency. (A) Represents native speakers, while (B) represents nonnative speakers of Superior proficiency, and (C) represents nonnative speakers of advanced proficiency.
Figure 2
Figure 2
Mean RTs of pseudo-semantic priming trials, semantic trials, and unrelated control trials split by language group for words of high and low frequency in Experiment 2.

Similar articles

Cited by

References

    1. Baayen H. (2008). Analyzing Linguistic Data: A Practical Introduction to Statistics Using R. Cambridge, UK: Cambridge University Press.
    1. Baayen H., Davidson D., Bates D. (2008). Mixed-effects modeling with crossed random effects for subjects and items. J. Mem. Lang. 59, 390–412. 10.1016/j.jml.2007.12.005 - DOI
    1. Bates D., Maechler M., Bolker B., Walker S. (2015). lme4: Linear Mixed-Effects Models using Eigen and S4. R Package Version 1.1-9. Available online at: http://CRAN.Rproject.org/package=lme4
    1. Beijering K., Gooskens C., Heeringa W. (2008). Predicting intelligibility and perceived linguistic distance by means of the Levenshtein algorithm, in Linguistics in the Netherlands, eds van Koppen M., Botma B. (Amsterdam: John Benjamins; ), 13–24.
    1. Best C. T. (1994). The emergence of native-language infuence in infants: a perceptual assimilation model, in The Transition from Speech Sounds to Spoken Words: The Development of Speech Perception, eds Nusbaum H., Goodman J., Howard C. (Cambridge, MA: MIT Press; ), 167–224.