MultiWOZ 2.3: A Multi-domain Task-Oriented Dialogue Dataset Enhanced with Annotation Corrections and Co-Reference Annotation

Autor:	Wei Peng, Ting Han, Ryuichi Takanobu, Dazhen Wan, Minlie Huang, Chongxuan Huang, Ximing Liu, Yixin Lian
Rok vydání:	2021
Předmět:	Computer science business.industry Natural language understanding computer.software_genre Consistency (database systems) Annotation Multi domain Task oriented Dialogue acts Artificial intelligence State (computer science) business computer Natural language processing
Zdroj:	Natural Language Processing and Chinese Computing ISBN: 9783030884826 NLPCC (2)
Popis:	Task-oriented dialogue systems have made unprecedented progress with multiple state-of-the-art (SOTA) models underpinned by a number of publicly available MultiWOZ datasets. Dialogue state annotations are error-prone, leading to sub-optimal performance. Various efforts have been put in rectifying the annotation errors presented in the original MultiWOZ dataset. In this paper, we introduce MultiWOZ 2.3, in which we differentiate incorrect annotations in dialogue acts from dialogue states, identifying a lack of co-reference when publishing the updated dataset. To ensure consistency between dialogue acts and dialogue states, we implement co-reference features and unify annotations of dialogue acts and dialogue states. We update the state of the art performance of natural language understanding and dialogue state tracking on MultiWOZ 2.3, where the results show significant improvements than on previous versions of MultiWOZ datasets (2.0–2.2).
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6d3475c6e40688c21f36195dbc11eeb0 https://doi.org/10.1007/978-3-030-88483-3_16 Zobrazit plný text záznamu