Schema-Guided User Satisfaction Modeling for Task-Oriented Dialogues
Yue Feng, Yunlong Jiao, Animesh Prasad, Nikolaos Aletras, Emine Yilmaz, Gabriella Kazai
摘要
User Satisfaction Modeling (USM) is one of the popular choices for task-oriented dialogue systems evaluation, where user satisfaction typically depends on whether the user's task goals were fulfilled by the system. Task-oriented dialogue systems use task schema, which is a set of task attributes, to encode the user's task goals. Existing studies on USM neglect explicitly modeling the user's task goals fulfillment using the task schema. In this paper, we propose SG-USM, a novel schema-guided user satisfaction modeling framework. It explicitly models the degree to which the user's preferences regarding the task attributes are fulfilled by the system for predicting the user's satisfaction level. SG-USM employs a pre-trained language model for encoding dialogue context and task attributes. Further, it employs a fulfillment representation layer for learning how many task attributes have been fulfilled in the dialogue, an importance predictor component for calculating the importance of task attributes. Finally, it predicts the user satisfaction based on task attribute fulfillment and task attribute importance. Experimental results on benchmark datasets (i.e. MWOZ, SGD, ReDial, and JDDC) show that SG-USM consistently outperforms competitive existing methods. Our extensive analysis demonstrates that SG-USM can improve the interpretability of user satisfaction modeling, has good scalability as it can effectively deal with unseen tasks and can also effectively work in low-resource settings by leveraging unlabeled data. 1 * Work done while Yue Feng was an intern at Amazon, Alexa Shopping. 1 Code is available at https://github.com/amzn/ user-satisfaction-modeling . Dialogue User's Task Goal Schema for Restaurant Task I'd like to look for a diner in Vacaville. I am searching for one that is intermediate priced. Japanese Restaurant is a lovely diner around there. That's prefect! Thanks! It's my pleasure.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper8
- Towards Scalable Multi-Domain Conversational Agents: The Schema-Guided Dialogue DatasetAbhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta 等AAAI 2020 · 被引用 707 次
- A Simple Language Model for Task-Oriented DialogueEhsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, Semih Yavuz 等NeurIPS 2020 · 被引用 590 次
- Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue SystemYixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta 等ACL 2022 · 被引用 218 次
- Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented DialogLibo Qin, Xiao Xu, Wanxiang Che, Yue Zhang 等ACL 2020 · 被引用 90 次
- GraphDialog: Integrating Graph Knowledge into End-to-End Task-Oriented Dialogue SystemsShiquan Yang, Rui Zhang, Sarah M. ErfaniEMNLP 2020 · 被引用 46 次
相关 Paper
- User Satisfaction Estimation with Sequential Dialogue Act Modeling in Goal-oriented Conversational SystemsYang Deng, Wenxuan Zhang, Wai Lam, Hong Cheng 等WWW 2022 · 被引用 34 次
- Interpretable User Satisfaction Estimation for Conversational Systems with Large Language ModelsYing-Chun Lin, Jennifer Neville, Jack W. Stokes, Longqi Yang 等ACL 2024 · 被引用 11 次
- Dialogue State Tracking with a Language Model using Schema-Driven PromptingChia-Hsuan Lee, Hao Cheng, Mari OstendorfEMNLP 2021 · 被引用 87 次
- A Speaker Turn-Aware Multi-Task Adversarial Network for Joint User Satisfaction Estimation and Sentiment AnalysisKaisong Song, Yangyang Kang, Jiawei Liu, Xurui Li 等AAAI 2023 · 被引用 5 次
- Rethinking the Evaluation of Dialogue Systems: Effects of User Feedback on Crowdworkers and LLMsClemencia Siro, Mohammad Aliannejadi, Maarten de RijkeSIGIR 2024 · 被引用 3 次
