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Phonology Circle - Craig Thorburn, A reinforcement learning approach to speech category acquisition

PhD student presenting his qualifying paper over zoom with a green-screened background of his data.

Phonology Circle - Craig Thorburn, A reinforcement learning approach to speech category acquisition

Linguistics Friday, October 1, 2021 2:00 pm - 3:00 pm

Friday October 1, Craig will practice his poster presentation for the Boston University Conference on Language Development, "A reinforcement learning approach to speech category acquisition," which reports joint work with Naomi and Ellen


Abstract

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 (Harmon et al., 2019; Lim et al., 2019). We formalize this hypothesis computationally and confirm that our reinforcement learning model simulates adult data from Lim and Holt (2011). Moreover, we show that the same model captures infant data from conditioned headturn experiments (Kuhl, 1983), suggesting that reinforcement learning could play a key role in speech category learning in infants as well as adults.

Add to Calendar 10/01/21 2:00 PM 10/01/21 3:00 PM America/New_York Phonology Circle - Craig Thorburn, A reinforcement learning approach to speech category acquisition

Friday October 1, Craig will practice his poster presentation for the Boston University Conference on Language Development, "A reinforcement learning approach to speech category acquisition," which reports joint work with Naomi and Ellen


Abstract

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 (Harmon et al., 2019; Lim et al., 2019). We formalize this hypothesis computationally and confirm that our reinforcement learning model simulates adult data from Lim and Holt (2011). Moreover, we show that the same model captures infant data from conditioned headturn experiments (Kuhl, 1983), suggesting that reinforcement learning could play a key role in speech category learning in infants as well as adults.

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Link to PHON page with Zoom link