@inproceedings{strathearn-gkatzia-2021-chefbot,
    title = "Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems",
    author = "Strathearn, Carl  and
      Gkatzia, Dimitra",
    editor = "Belz, Anya  and
      Fan, Angela  and
      Reiter, Ehud  and
      Sripada, Yaji",
    booktitle = "Proceedings of the 14th International Conference on Natural Language Generation",
    month = aug,
    year = "2021",
    address = "Aberdeen, Scotland, UK",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2021.inlg-1.5/",
    doi = "10.18653/v1/2021.inlg-1.5",
    pages = "46--47",
    abstract = "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-to-human conversations are enhanced by not only the latest utterance of the interlocutor, but also by recalling relevant information about concepts/objects covered in the dialogue and integrating them into their responses. 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 \textit{commonsense} capabilities by offering explanations of how objects can be used and provide recommendations for replacing ingredients."
}