Success and failure in teaching the [r]-[l] contrast to Japanese adults: Tests of a Hebbian model of plasticity and stabilization in spoken language perception

• Published in: Cognitive, affective, & behavioral neuroscience affective, & behavioral neuroscience, 2002-06, Vol.2 (2), p.89-108
• Main Authors: MCCANDUSS, Bruce D, FIEZ, Julie A, PROTOPAPAS, Athanassios, CONWAY, Mary, MCCLELLAND, James L
• Format: Article
• Language: English
• Subjects: Adult; Biological and medical sciences; Discrimination Learning; Feedback; Fundamental and applied biological sciences. Psychology; Humans; Language; Neuronal Plasticity - physiology; Phonetics; Production and perception of spoken language; Psychological Theory; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Random Allocation; Speech Discrimination Tests; Speech Perception; Teaching - methods; Teaching - standards; Verbal Learning
• ISSN: 1530-7026; 1531-135X
• DOI: 10.3758/cabn.2.2.89

A Hebbian model of learning predicts that adults may be able to acquire a nonnative speech contrast if they are trained with stimuli that are exaggerated to make them perceptually distinct. To test these ideas, we asked Japanese adults to identify contrasting [r]-[l] stimuli (e.g., rock-lock) in two training conditions. In the adaptive condition, the [r]-[l] contrast was exaggerated at first and then adjusted to maintain accurate identification. In the fixed condition, a fixed pair of stimuli were used that were distinguishable by native English speakers but difficult for the Japanese learners to discriminate. To examine whether feedback contributes to learning, we ran separate groups with and without feedback in the fixed and the adaptive conditions. Without feedback, 3 days of adaptive training produced substantial improvements, but 3 days of fixed training produced no benefit relative to control, consistent with the Hebbian account. With feedback, both fixed and adaptive training led to robust improvements, and the benefit of training transferred to a second continuum (e.g., road-load). The results are consistent with Hebbian models that are augmented to be sensitive to feedback.