PhD Position F/M The role of rapport in human-conversational agent interaction: Modeling conversation to improve task performance in human-agent interaction
Contexte et atouts du poste
The objective of this project is to build embodied conversational agents (also known as ECAs, or virtual humans, or chatbots, or multimodal dialogue systems) that have the ability to engage their users in both social and task talk, where the social talk serves to improve task performance.
In order to achieve this objective, we model human-human conversation, and integrate the models into ECAs, and then evaluate their performance.
This project is located at the prestigious computer science institute INRIA in downtown Paris. It takes place in the context of the PRAIRIE Institute for Interdisciplinary Research on AI - one of the four 3IA institutes launched by the French government in 2019. For more information see
Mission confiée
The doctoral student chosen for this project will acquire a broad range of skills in the analysis and synthesis of conversational behavior.
S / he will build a corpus of data on the social aspects of human-human conversation within a particular domain, and annotate and analyze those data.
He or she will derive computational models from the results of the data analysis as well as based on relevant prior literature, and refine those models using structural equation modeling and other tools.
The doctoral student will integrate the computational models of social phenomena into a functioning ECA using machine learning approaches to dialogue systems, such as deep reinforcement learning and LSTM (among others), and will evaluate whether integrating the new models improves the performance of the ECA.
Applications of the work will be as varied as virtual personal assistants such as Alexa, Siri, and Google Now and intelligent tutoring systems.
For more information on the project, potential candidates should look at the SARA (Socially-Aware Robot Assistant) website at
Principales activités
- Design and carry out experiments
- Analyze their results
- Implement modules in working socially-aware dialogue systems
- Write articles
- Present work in conferences
- write a doctoral thesis
Compétences
Technical skills and level required :
Solid competence in deep learning applied to language (prior experience working with dialogue systems is a strong plus), competence in statistics, avanced competence in programming in language such as Python and C++, and use of tools such as Tensorflow and Pytorch.
Languages : French and English
French and English
Relational skills :
ability to work in a team, and collaborate with others from different disciplines and backgrounds.
Other valued appreciated :
Theoretical background in one or several of the following : cognitive science, linguistics, conversational analysis, sociolinguistics, social cognition, learning science.
Avantages
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave : 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
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