Adults struggle to learn non-native speech categories in many experimental settings (Goto, 1971), but learn efficiently in a video game paradigm where non-native speech sounds have functional significance (Lim and Holt, 2011). Behavioral and neural evidence from this and other paradigms point toward the involvement of reinforcement learning mechanisms in speech category learning. We formalize this hypothesis computationally and present two simulations. The first simulates the findings of Lim et al. (2019), providing proof in principle that a reinforcement learning algorithm can successfully capture human results in a video game where people are learning novel categories of noise tokens. Our second simulation extends this to speech sounds and demonstrates that our algorithm mimics second language learners’ improvement on discrimination of a non-native speech contrast. Together these two simulations show that reinforcement learning provides an accurate model of human learning in this paradigm and provide evidence supporting the hypothesis that this mechanism could play a key role in effective speech category learning in adults. Being able to identify the algorithms employed in this paradigm could provide many avenues for pedagogical changes in second language learning and let teachers harness the processes that allow for efficient learning and improvement of non-native perceptual ability.
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This content will become publicly available on June 10, 2025
Individual differences in working memory impact the trajectory of non-native speech category learning
What is the role of working memory over the course of non-native speech category learning? Prior work has predominantly focused on how working memory might influence learning assessed at a single timepoint. Here, we substantially extend this prior work by examining the role of working memory on speech learning performance over time (i.e., over several months) and leverage a multifaceted approach that provides key insights into how working memory influences learning accuracy, maintenance of knowledge over time, generalization ability, and decision processes. We found that the role of working memory in non-native speech learning depends on the timepoint of learning and whether individuals learned the categories at all. Among learners, across all stages of learning, working memory was associated with higher accuracy as well as faster and slightly more cautious decision making. Further, while learners and non-learners did not have substantially different working memory performance, learners had faster evidence accumulation and more cautious decision thresholds throughout all sessions. Working memory may enhance learning by facilitating rapid category acquisition in initial stages and enabling faster and slightly more careful decision-making strategies that may reduce the overall effort needed to learn. Our results have important implications for developing interventions to improve learning in naturalistic language contexts.
more » « less- Award ID(s):
- 1953712
- PAR ID:
- 10543531
- Editor(s):
- Souza, Alessandra S
- Publisher / Repository:
- PLOS
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 19
- Issue:
- 6
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0297917
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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