{"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/towards-universal-dialogue-state-tracking","title":"Towards Universal Dialogue State Tracking","arxiv_id":"1810.09587","date":"2018-10-22","proceeding":"EMNLP 2018 10","authors":["Liliang Ren","Kaige Xie","Lu Chen","Kai Yu"],"abstract":"Dialogue state tracking is the core part of a spoken dialogue system. It\nestimates the beliefs of possible user's goals at every dialogue turn. However,\nfor most current approaches, it's difficult to scale to large dialogue domains.\nThey have one or more of following limitations: (a) Some models don't work in\nthe situation where slot values in ontology changes dynamically; (b) The number\nof model parameters is proportional to the number of slots; (c) Some models\nextract features based on hand-crafted lexicons. To tackle these challenges, we\npropose StateNet, a universal dialogue state tracker. It is independent of the\nnumber of values, shares parameters across all slots, and uses pre-trained word\nvectors instead of explicit semantic dictionaries. Our experiments on two\ndatasets show that our approach not only overcomes the limitations, but also\nsignificantly outperforms the performance of state-of-the-art approaches.","url_abs":"http://arxiv.org/abs/1810.09587v1","url_pdf":"http://arxiv.org/pdf/1810.09587v1.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":"towards-universal-dialogue-state-tracking","repo_url":"https://github.com/renll/StateNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"mxnet","reach":null}],"tasks":[{"task_slug":"dialogue-state-tracking","task_name":"Dialogue State Tracking"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/dialogue-state-tracking-on-second-dialogue","task":"Dialogue State Tracking","dataset":"Second dialogue state tracking challenge","model":"StateNet","rank_in_archive_order":2,"of":7,"metrics":{"Joint":"75.5"},"uses_additional_data":false},{"leaderboard":"/sota/dialogue-state-tracking-on-wizard-of-oz","task":"Dialogue State Tracking","dataset":"Wizard-of-Oz","model":"StateNet","rank_in_archive_order":5,"of":10,"metrics":{"Joint":"88.9"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1810.09587","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}