Chat, Shift and Perform: Bridging the Gap between Task-oriented and Non-task-oriented Dialog Systems
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Abstract (arXiv)
We propose CASPER (ChAt, Shift and PERform), a novel dialog system consisting of three types of dialog models: chatter, shifter, and performer. Shifter, which is designed for topic switching, enables a seamless flow of dialog from open-domain chat- to task-oriented dialog. In a user study, CASPER gave a better impression in terms of naturalness of response, lack of forced topic switching, and satisfaction compared with a baseline dialog system trained in an end-to-end manner. In an ablation study, we found that naturalness of response, dialog satisfaction, and task-elicitation rate improved compared with when shifter was removed from CASPER, indicating that topic shift with shifter supports the introduction of natural task-oriented dialog.
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References · 8
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2015A Neural Conversational Modelcited by 195
- 2019Leveraging Pre-trained Checkpoints for Sequence Generation Taskscited by 182
- 2019Towards Knowledge-Based Recommender Dialog Systemcited by 112
- 2016Learning End-to-End Goal-Oriented Dialogcited by 104
- 2020CR-Walker: Tree-Structured Graph Reasoning and Dialog Acts for Conversational Recommendationcited by 31
- 2017Generative Encoder-Decoder Models for Task-Oriented Spoken Dialog Systems with Chatting Capabilitycited by 14
- 2017Chat Detection in an Intelligent Assistant: Combining Task-oriented and Non-task-oriented Spoken Dialogue Systemscited by 8
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