Intelligent Assisting Conversational Agents Viewed through Novice Users’ Requests

Assisting Conversational Agents are Embodied Conversational Agents dedicated to the Function of Assistance for applications and services to the general public, especially on the Internet. We have developed a web-based framework to experiment with assisting agents regarding the key issue of believability, and where good Natural Language Understanding is a primary concern. Now, we are confronted with the difficult issue of the cost of developing and customizing Natural Language Processing tools (NLP-tools) for each new assisted application. In this paper, we propose an approach which is a tradeoff between complex dialogue systems and naive chatbot systems. We think that our approach is worth considering because it focuses on a concise and well circumscribed linguistic domain: the domain of Assistance Requests that we captured by registering a corpus, in various contexts with ordinary people placed in front of Assisting Conversational Agents.