Existing task-oriented dialogue systems seldom emphasize multi-intent scenarios, which makes them hard to track complex intent switch in a multi-turn dialogue, and even harder to make proactive reactions for the user\u2019s next potential intent. In this paper, we formalize the multi-intent tracking task and introduce a complete set of intent switch modes. Then we propose ISwitch, a system that can handle complex multi-intent dialogue interactions. In this system, we design a gated controller to recognize the current intent, and a proactive mechanism to predict the next potential intent. Based on these, we use pre-defined patterns to generate proper responses. Experiments show that our model can achieve high intent recognition accuracy, and simplify the dialogue process. We also construct and release a new dataset for complex multi-turn multi-intent-switch dialogue.<\/p>\n","protected":false},"excerpt":{"rendered":"
Existing task-oriented dialogue systems seldom emphasize multi-intent scenarios, which makes them hard to track complex intent switch in a multi-turn dialogue, and even harder to make proactive reactions for the user\u2019s next potential intent. In this paper, we formalize the multi-intent tracking task and introduce a complete set of intent switch modes. 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