Phd on neural alignment between speakers in conversational interactions

Does prediction drive neural alignment in conversation?

Objectives:

Recent studies on neural alignment in language have shown that successful communication relies on the synchronization of the same brain regions in both speakers. However, more explicit links between neural alignment and specific linguistic functions remain to be established. ESR3’s project relies on the hypothesis that the degree of neural synchronization depends on the degree of predictive processing: the more predictability between speaker and listener (e.g. by modulating meaning predictability, syntactic familiarity, or speaker dialect), the more their brain responses will align and display similar oscillatory dynamics. This will be tested for specific linguistic functions in dual-EEG experiments with pairs of interlocutors engaged in conversations. The identification of component-specific brain markers of predictability and alignment will allow to establish which linguistic factors can enhance the predictability, and thus alignment, in human-machine interactions.

Expected results:

• Establish whether neural alignment is dependent on inter-speaker predictability;
• Obtain neurophysiological measurements of predictability in conversation;
• Identify for different linguistic functions the time course of neural alignment and oscillatory dynamics in perception-production interactions;
• Apply these neural markers of inter-speaker predictability and alignment as an evaluation tool for the assessment of the human-likeness of human-machine interactions.

Based in Aix-en-Provence, France

Full-time three-year contract, starting September 2020

PhD enrolment at: Aix-Marseille University

Main supervisor’s institution: Aix-Marseille University

Main supervisor: Dr Kristof Strijkers

Secondments:

• Freie Universität Berlin: explore how predictive alignment interacts with different verbal acts and pragmatic contexts (5 months);
• Furhat Robotics, Stockholm: apply neurophysiological insights of predictability and neural alignment to test and improve the effectiveness of human-machine interactions (6 months).

Co-supervisors’ institutions:

•     Freie Universität Berlin, Germany
•     Furhat Robotics, Stockholm, Sweden