Journal Paper

The journal paper describing the main challenges of the project is accepted and now available : Clavel, C., Labeau, M., & Cassell, J. (2023). Socio-conversational Systems: Three Challenges at the Crossroads of Fields. Frontiers in Robotics and AI, 336.

Socio-conversational systems are dialogue systems, including what are sometimes referred to as chatbots, vocal assistants, social robots, and embodied conversational agents, that are capable of interacting with humans in a way that treats both the specifically social nature of the interaction and the content of a task. The aim of this paper is twofold: 1) to uncover some places where the compartmentalized nature of research conducted around socio-conversational systems creates problems for the field as a whole, and 2) to propose a way to overcome this compartmentalization and thus strengthen the capabilities of socio-conversational systems by defining common challenges. Specifically, we examine research carried out by the signal processing, natural language processing and dialogue, machine/deep learning, social/affective computing and social sciences communities. We focus on three major challenges for the development of effective socio-conversational systems, and describe ways to tackle them.

Chloé Clavel
Chloé Clavel
Research Director in Social Computing

My research interests are in the areas of Affective Computing and Artificial Intelligence that lie at the crossroad of multiple disciplines including, speech and natural language processing, machine learning, and social robotics. I study computational models of socio-emotional behaviors (e.g., sentiments, social stances, engagement, trust) in interactions be it human-human interactions (social networks, job interviews) or human-agent interactions (conversational agents, social robots).