Abstracts 2005 - The Psychonomic Society

Saturday Evening Posters 5121–5122
event, and sentences with an impossible and unlikely event. Sentences
had the same words in critical regions and were normed for both possibility
and likelihood. Results suggested that event likelihood and
possibility had differential effects in the eye movement record. Results
will be discussed in relation to Hagoort et al.’s (2004) ERP results.
(5121)
The Relative Importance of Language Factors in Word Skipping
During Reading. DENIS DRIEGHE & TIMOTHY DESMET, Ghent
University, & MARC BRYSBAERT, University of London (sponsored
by Robert Hartsuiker)—The skipping probability of a word is influenced
by its processing ease (e.g., predictability). Meta-analyses examining
these influences report effect sizes across studies ranging
from 0% to 13%, with an average of 8%. One study does not fit this
picture: Vonk (1984) reported 23% more skipping of the pronoun
(she) in Sentence 1 (Mary was envious of Helen because she never
looked so good), in which the pronoun had no disambiguating value,
than in Sentence 2 (Mary was envious of Albert because she never
looked so good), where it did. We reexamined this ambiguity in Dutch
and observed only an 8% skipping difference. Our results also show
that when the pronoun was masculine (hij [he]), it was skipped 10%
more often than the feminine pronoun (zij [she]), probably due to the
141
fact that in Dutch, the feminine pronoun can also be plural (they),
making it potentially ambiguous.
(5122)
Interaction in Models of Spoken Word Recognition. JAMES S.
MAGNUSON, TED STRAUSS, & HARLAN D. HARRIS, University
of Connecticut—A long-standing debate in spoken word recognition
concerns information flow: Is there feedback from lexical to sublexical
representations, or does information only flow forward? Proponents
of feedforward models cite Frauenfelder and Peeters (1998;
FP98) as evidence that even in TRACE, an interactive model, feedback
serves no functional role (aside from accounting for lexical influences
on sublexical decisions). FP98 tested recognition time in
TRACE for 21 words with lexical feedback on and off. About half
were recognized more quickly without feedback. We revisited this result
to see whether it generalizes to all words and whether feedback
protects the model against noise. We tested all words in a 901-word
lexicon under multiple levels of noise. Without noise, 73% of the
words were recognized faster with feedback (we will discuss neighborhood
characteristics of items recognized faster without feedback).
With noise, both accuracy and response times were significantly better
with feedback. In short, feedback helps.