Abstract
There is ample evidence showing that listeners are able to quickly adapt their phoneme classes to ambiguous sounds using a process called lexically-guided perceptual learning. This paper presents the first attempt to examine the neural correlates underlying this process. Specifically, we compared the brain's responses to ambiguous [f/s] sounds in Dutch non-native listeners of English (N=36) before and after exposure to the ambiguous sound to induce learning, using Event-Related Potentials (ERPs). We identified a group of participants who showed lexically-guided perceptual learning in their phonetic categorization behavior as observed by a significant difference in /s/ responses between pretest and posttest and a group who did not. Moreover, we observed differences in mean ERP amplitude to ambiguous phonemes at pretest and posttest, shown by a reliable reduction in amplitude of a positivity over medial central channels from 250 to 550 ms. However, we observed no significant correlation between the size of behavioral and neural pre/posttest effects. Possibly, the observed behavioral and ERP differences between pretest and posttest link to different aspects of the sound classification task. In follow-up research, these differences will be further investigated by assessing their relationship to neural responses to the ambiguous sounds in the exposure phase.
Original language | English (US) |
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Pages (from-to) | 1223-1227 |
Number of pages | 5 |
Journal | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH |
Volume | 2019-September |
DOIs | |
State | Published - 2019 |
Event | 20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019 - Graz, Austria Duration: Sep 15 2019 → Sep 19 2019 |
Keywords
- Adaptation
- ERP
- Human speech processing
- Lexically-guided perceptual learning
- Neural correlates
ASJC Scopus subject areas
- Language and Linguistics
- Human-Computer Interaction
- Signal Processing
- Software
- Modeling and Simulation