The Time-Invariant String Kernel (TISK) model of spoken word recognition (Hannagan, Magnuson & Grainger, 2013; You & Magnuson, 2018) is an interactive activation model with many similarities to TRACE (McClelland & Elman, 1986). However, by replacing most time-specific nodes in TRACE with time-invariant open-diphone nodes, TISK uses orders of magnitude fewer nodes and connections than TRACE. Although TISK performed remarkably similarly to TRACE in simulations reported by Hannagan et al., the original TISK implementation did not include lexical feedback, precluding simulation of top-down effects, and leaving open the possibility that adding feedback to TISK might fundamentally alter its performance. Here, we demonstrate that when lexical feedback is added to TISK, it gains the ability to simulate top-down effects without losing the ability to simulate the fundamental phenomena tested by Hannagan et al. Furthermore, with feedback, TISK demonstrates graceful degradation when noise is added to input, although parameters can be found that also promote (less) graceful degradation without feedback. We review arguments for and against feedback in cognitive architectures, and conclude that feedback provides a computationally efficient basis for robust constraint-based processing.
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Do They Know It's Christmash? Lexical Knowledge Directly Impacts Speech Perception
Abstract We recently reported strong, replicable (i.e., replicated) evidence forlexically mediated compensation for coarticulation(LCfC; Luthra et al., 2021), whereby lexical knowledge influences a prelexical process. Critically, evidence for LCfC provides robust support forinteractivemodels of cognition that includetop‐down feedbackand is inconsistent withautonomousmodels that allow only feedforward processing. McQueen, Jesse, and Mitterer (2023) offer five counter‐arguments against our interpretation; we respond to each of those arguments here and conclude that top‐down feedback provides the most parsimonious explanation of extant data.
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- Award ID(s):
- 2043903
- PAR ID:
- 10509740
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Cognitive Science
- Volume:
- 48
- Issue:
- 5
- ISSN:
- 0364-0213
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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