Seminar on “speech production and perception”

Prof. F. Guenther and REaDY team, LPL (5-6 May)

Thursday, May 5^th 2022

Discussion with Prof. F. Guenther around the following presentations

14h-14h40 : Noël Nguyen & Kristof Strijkers : Phonetic and semantic convergence in speech communication

14h40-15h10 : Serge Pinto: Studying speech motor control from its impairment: the cases of hypo- and hyperkinetic dysarthrias

15h10-15h30 : Coffee break

15h30-16h10 : Elin Runnqvist, Lydia Dorokhova & Snezana Todorović : Action monitoring from tongue movements to words

16h10-16h40 : Anne-Sophie Dubarry : Exploring the variability of neurophysiological data during language processing

Friday, May 6^th 2022, 10h30-12h00

KEYNOTE by Prof. F. Guenther

(Director of Speech Neuroscience Lab, Boston University)

Neurocomputational modeling of speech production

Speech production is a highly complex sensorimotor task involving tightly coordinated processing in the frontal, temporal, and parietal lobes of the cerebral cortex. To better understand these processes, our laboratory has designed, experimentally tested, and iteratively refined a neural network model, called the DIVA model, whose components correspond to the brain regions involved in speech. Babbling and imitation phases are used to train neural mappings between phonological, articulatory, auditory, and somatosensory representations. After the imitation phase, the model can produce learned phonemes and syllables by generating movements of an articulatory synthesizer. An extended version of the model, called GODIVA, addresses the neural circuitry underlying the buffering and sequencing of phonological units in multi-syllabic utterances. Because the model’s components correspond to neural populations and are given precise anatomical locations, activity in the model’s neurons can be compared directly to neuroimaging data. Computer simulations of the model account for a wide range of experimental findings, including data on acquisition of speaking skills, articulatory kinematics, and brain activity during normal and perturbed speech. Furthermore, “damaged” versions of the model are being used to investigate several communication disorders, including stuttering, apraxia of speech, and hypokinetic dysarthria