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Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems

Strathearn, Carl; Gkatzia, Dimitra

Authors



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 commonsense capabilities by offering explanations of how objects can be used and provide recommendations for replacing ingredients.

Presentation Conference Type Conference Paper (Published)
Conference Name 14th International Conference on Natural Language Generation
Publication Date 2021
Deposit Date Dec 2, 2022
Publisher Association for Computational Linguistics (ACL)
Pages 46-47
Book Title Proceedings of the 14th International Conference on Natural Language Generation
Public URL http://researchrepository.napier.ac.uk/Output/2969151
Publisher URL https://aclanthology.org/2021.inlg-1.5