{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-network-based-end-to-end-trainable-task","title":"A Network-based End-to-End Trainable Task-oriented Dialogue System","arxiv_id":"1604.04562","date":"2016-04-15","proceeding":"EACL 2017 4","authors":["Tsung-Hsien Wen","David Vandyke","Nikola Mrksic","Milica Gasic","Lina M. Rojas-Barahona","Pei-Hao Su","Stefan Ultes","Steve Young"],"abstract":"Teaching machines to accomplish tasks by conversing naturally with humans is\nchallenging. Currently, developing task-oriented dialogue systems requires\ncreating multiple components and typically this involves either a large amount\nof handcrafting, or acquiring costly labelled datasets to solve a statistical\nlearning problem for each component. In this work we introduce a neural\nnetwork-based text-in, text-out end-to-end trainable goal-oriented dialogue\nsystem along with a new way of collecting dialogue data based on a novel\npipe-lined Wizard-of-Oz framework. This approach allows us to develop dialogue\nsystems easily and without making too many assumptions about the task at hand.\nThe results show that the model can converse with human subjects naturally\nwhilst helping them to accomplish tasks in a restaurant search domain.","url_abs":"http://arxiv.org/abs/1604.04562v3","url_pdf":"http://arxiv.org/pdf/1604.04562v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-network-based-end-to-end-trainable-task","repo_url":"https://github.com/ysglh/Task-Oriented-Dialogue-Dataset-Survey","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"task-oriented-dialogue-systems","task_name":"Task-Oriented Dialogue Systems"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1604.04562","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}