An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions

eLife

Andrea E Martin¹  Sanne ten Oever² 

[1] Language and Computation in Neural Systems group, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands;Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands;Language and Computation in Neural Systems group, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands;Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands;Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands;

关键词: speech;    oscillations;    language;    temporal processing;    prediction;    None;   

DOI  :  10.7554/eLife.68066

来源: eLife Sciences Publications, Ltd

【 摘 要 】

Neuronal oscillations putatively track speech in order to optimize sensory processing. However, it is unclear how isochronous brain oscillations can track pseudo-rhythmic speech input. Here we propose that oscillations can track pseudo-rhythmic speech when considering that speech time is dependent on content-based predictions flowing from internal language models. We show that temporal dynamics of speech are dependent on the predictability of words in a sentence. A computational model including oscillations, feedback, and inhibition is able to track pseudo-rhythmic speech input. As the model processes, it generates temporal phase codes, which are a candidate mechanism for carrying information forward in time. The model is optimally sensitive to the natural temporal speech dynamics and can explain empirical data on temporal speech illusions. Our results suggest that speech tracking does not have to rely only on the acoustics but could also exploit ongoing interactions between oscillations and constraints flowing from internal language models.

【 授权许可】

CC BY