The clustering coefficient of phonological neighborhoods influences spoken word recognition

2006 ◽  
Vol 120 (5) ◽  
pp. 3252-3252 ◽  
Author(s):  
Michael Vitevitch
Keyword(s):  
Word Recognition ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Clustering Coefficient ◽  
Phonological Neighborhoods

scholarly journals Clustering coefficients of lexical neighborhoods

2010 ◽  
Vol 5 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Nicholas Altieri ◽  
Thomas Gruenenfelder ◽  
David B. Pisoni
Keyword(s):  
Word Recognition ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Neighborhood Density ◽  
Clustering Coefficient ◽  
Response Latencies ◽  
Graph Theoretic ◽  
Word Repetition ◽  
Lexical Neighborhoods ◽  
Speed And Accuracy

High neighborhood density reduces the speed and accuracy of spoken word recognition. The two studies reported here investigated whether Clustering Coefficient (CC) — a graph theoretic variable measuring the degree to which a word’s neighbors are neighbors of one another, has similar effects on spoken word recognition. In Experiment 1, we found that high CC words were identified less accurately when spectrally degraded than low CC words. In Experiment 2, using a word repetition procedure, we observed longer response latencies for high CC words compared to low CC words. Taken together, the results of both studies indicate that higher CC leads to slower and less accurate spoken word recognition. The results are discussed in terms of activation-plus-competition models of spoken word recognition.

Tracking the time course of lexical access in spoken word recognition

1997 ◽  
Author(s):  
Paul D. Allopenna ◽  
James S. Magnuson ◽  
Michael K. Tanenhaus
Keyword(s):  
Word Recognition ◽  
Lexical Access ◽  
Time Course ◽  
Spoken Word Recognition ◽  
Spoken Word
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