A Multimodal Conversational Agent for Personalized Language Learning

Conversational agents have became a strong alternative to enhance educational systems with intelligent communicative capabilities. In this paper, we describe a multimodal conversational agent that facilitates an independent and user-adapted second language learning. The different modules of the system cooperate to interact with students using spoken natural language and visual modalities, and adapt their functionalities taking into account their evolution and specific preferences. The results of a preliminary evaluation show that users’ satisfaction with the system was high, as well as the perceived didactic potential and adaptive functionalities.