DIANA, an end-to-end computational model of human word comprehension
This paper presents DIANA, a new computational
model of human speech processing. It is the first
model that simulates the complete processing chain
from the on-line processing of an acoustic signal
to the execution of a response, including reaction
times. Moreover it assumes minimal modularity.
DIANA consists of three components. The activation
component computes a probabilistic match between
the input acoustic signal and representations
in DIANA’s lexicon, resulting in a list of word hypotheses
changing over time as the input unfolds.
The decision component operates on this list and selects
a word as soon as sufficient evidence is available.
Finally, the execution component accounts for
the time to execute a behavioral action.
We show that DIANA well simulates the average
participant in a word recognition experiment.
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