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PANORAMA

The key concept of this project is “user adaptive AI in the context of human-computer interaction”. This project addresses two aspects for this concept. First, we will conduct research on user adaptivity of artificial intelligence embodied as a conversational agent. When people talk to other people, they change their verbal and nonverbal communication behaviors according to those of the partner. Therefore, user adaptivity is an essential issue in improving human-agent interaction.

Context

Communication style is also different depending on the culture, and adapting the agent behaviors to a target culture is useful. We will tackle this problem by employing a machine learning approach. However, a bottleneck of this approach is that annotating users’ multi-modal behaviors to create training data is time consuming. We will offer semi-automated annotations and provide visual feedback to inspect and correct machine-generated labels by incorporating eXplainable AI (XAI) techniques. Thus, the concept for user adaptive AI is used to support users in creating multimodal corpus as well as improve the human-agent interaction. Moreover, the concept of user adaptivity is also focused on the psychological studies in this project, in which user motivation will be investigated in one relevant use case (personalised motivational coaching for physical activity). Therefore, this project envisions a new research methodology for machine-learning-based conversational agents by focusing on the concept of user adaptivity.

Objectives

The PANORAMA project aims to accomplish the following 5 research goals:

Results

Adaptive AI interface impacts the economy and the future society.

First, user adaptive technology enhances the quality of human-computer interaction and this contributes to improve task performance and productivity of the users in industries.

Moreover, user adaptive AI will effectively motivate the users to adopt a healthy lifestyle in the long term, and this may change people’s lives in the future society.

Partnerships and collaborations

Project members

Catherine Pelachaud
Directrice de recherche CNRS
Catherine Achard
Professeure des Universités