months Post-Doc position (possibly extendable) in language processing for the automatic detection of speech disorders during awake brain surgery
- Brest, Finistère
- CDD
- Temps-plein
- Improve the accuracy of a first innovative approach based on deep learning for the detection of language deficits using a French and Japanese cross-language database [11]. A synthetic database will be created using existing approaches to potentially compensate for the lack of data [12] and Wave2Vec2-based Deep-Learning models will be investigated because of their efficiency and performances in other clinical contexts [13]. The improved method will be finally evaluated on the cross-language database and in a real awake neurosurgery context.
- Highlight the correlations between speech alteration and the exact location of the stimulation. Specific registration approaches will be used to propagate the patient's brain as well as their tumor on a latent space allowing the homogeneous representation of the stimulations in relation to the tumor and thus being able to create a functional or pathological anatomical atlas.
EURAXESS