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arXiv · 2304.00884

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

Yuncheng Hua·Xiangyu Xi·Zheng Jiang·Guanwei Zhang·Chaobo Sun·Guanglu Wan·Wei Ye
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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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Yuncheng Hua, Xiangyu Xi, Zheng Jiang, Guanwei Zhang, Chaobo Sun, Guanglu Wan, Wei Ye. 2023-04-03. Dialog-to-Actions: Building Task-Oriented Dialogue System via Action-Level Generation. https://arxiv.org/abs/2304.00884

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