Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems
Carl Strathearn, Dimitra Gkatzia · 2021
Conversational systems aim to generate responses that are accurate, relevant and engaging, either through utilising neural end-to-end models or through slot filling.Human-tohuman conversations are enhanced by not only the latest utterance of the interlocutor, but also by recalling and referring to relevant information about concepts/objects covered in the conversation so far.Such information may contain recent referred concepts, commonsense knowledge and more.A concrete scenario of such dialogues is the cooking scenario, i.e. when an artificial agent (personal assistant, robot, chatbot) and a human converse about a recipe.We will demo a novel system for commonsense enhanced response generation in the scenario of cooking, where the conversational system is able to not only provide directions for cooking step-by-step, but also display commonsense capabilities such as offering explanations on object use and recommending replacements of ingredients.