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Abstract:
A growing number of researchers have been using eye movements
during spoken language comprehension to investigate issues in
lexical access, parsing, and interpretation. However, a widespread
concern has been that this method may introduce distorted results
because it uses a closed set of visual alternatives. Moreover, the
interpretation of the eye movements depends on a plausible, but
relatively untested, assumption about the link between momentary
attentional shifts and saccadic eye movements. We present two
experiments which address these issues by showing that a simple
linking hypotheses between underlying activations in the TRACE
model and eye movements naturally accounts for some otherwise
puzzling results in the spoken word recognition literature. These
experiments also demonstrate clear effects of non-displayed
competitors. Moreover, they highlight the importance of using
explicit linking hypotheses, an issue that has relevance for a
number of issues in sentence processing.
Marslen-Wilson and Warren (1994) found that lexical-decision
latencies to cross-spliced word sequences whose initial CV portion
had been excised from an existing word (e.g., jo(g)b) did not
differ from latencies to word sequences excised from a nonword
(e.g., jo(d)b). They interpreted thisresult as strong evidence
against models incorporating lexical competition via lateral
inhibition. McQueen, Norris, and Cutler et al were able to simulate
the data in a model with competition, but only by choosing a
lexical decision threshold within an extremely restricted range.
However, mean lexical-decision latencies may not be an appropriate
measure of activation for the target 'job', because the activation
of its competitor 'jog' also influences the probability of
responding 'yes', making it difficult to relate lexical decisions
to the underlying activation functions. By contrast, tracking eye
movements can provide a continuous measure of lexical activation
over time.
Participants' eye movements to pictured objects were recorded as
they followed instructions to click on one of the four objects
(e.g., 'click on the net'). Allopenna, Magnuson and Tanenhaus
(1998) demonstrated that the proportion of fixations to each
picture over time, as the target word is heard, can be mapped onto
lexical-activation functions using a modified form of the classic
Luce choice rule.
The name of the target object was cross-spliced from another
token of itself (ne(t)t), from another word (ne(ck)t), or from a
nonword (ne(p)t). In Experiment 1, the competitor picture (neck)
was displayed along with the target picture and twounrelated
pictures. Fixations to the target over time indicated a fast rise
in the ne(t)t condition, intermediate in the ne(p)t condition,
andslowest in the ne(ck)t condition. The competitor picture was
fixated most in the ne(ck)t condition, intermediate in the ne(p)t
condition and least often the ne(t)t condition. The time course of
fixations to the target and competitor pictures mirrored
predictions generated from activations in a TRACE-style interactive
activation model, using the Allopenna et al. (1998) linking
hypothesis. Eliminating lexical competition significantly reduced
the fit between the model and the data. In Experiment 2, the
competitor picture was not displayed. Under these conditions, the
model predicted that the time course of fixations to the target
would be similar in the ne(p)t and ne(t)t conditions and slower in
the ne(ck)t condition. The data closely matched these predictions.
Finally, the model simulates the lexical-decision data across a
range of response thresholds under the assumption that a 'yes'
response is triggered probabilistically when either the target or
competitor reaches threshold.
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