Dialog-to-Actions: Building Task-Oriented Dialogue System via Action-Level Generation

• URL: http://arxiv.org/abs/2304.00884v1
• Date: Mon, 3 Apr 2023 11:09:20 GMT
• Title: Dialog-to-Actions: Building Task-Oriented Dialogue System via Action-Level Generation
• Authors: Yuncheng Hua, Xiangyu Xi, Zheng Jiang, Guanwei Zhang, Chaobo Sun, Guanglu Wan, Wei Ye
• Abstract summary: We propose a task-oriented dialogue system via action-level generation. Specifically, we first construct dialogue actions from large-scale dialogues and represent each natural language (NL) response as a sequence of dialogue actions. We train a Sequence-to-Sequence model which takes the dialogue history as input and outputs sequence of dialogue actions.
• Score: 7.110201160927713
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: End-to-end generation-based approaches have been investigated and applied in task-oriented dialogue systems. However, in industrial scenarios, existing methods face the bottlenecks of controllability (e.g., domain-inconsistent responses, repetition problem, etc) and efficiency (e.g., long computation time, etc). In this paper, we propose a task-oriented dialogue system via action-level generation. Specifically, we first construct dialogue actions from large-scale dialogues and represent each natural language (NL) response as a sequence of dialogue actions. Further, we train a Sequence-to-Sequence model which takes the dialogue history as input and outputs sequence of dialogue actions. The generated dialogue actions are transformed into verbal responses. Experimental results show that our light-weighted method achieves competitive performance, and has the advantage of controllability and efficiency.

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