Empathy is a crucial factor in open-domain conversations, which naturally shows one's caring and understanding to others. Though several methods have been proposed to generate empathetic responses, existing works often lead to monotonous empathy that refers to generic and safe expressions. In this paper, we propose to use explicit control to guide the empathy expression and design a framework DiffusEmp based on conditional diffusion language model to unify the utilization of dialogue context and attribute-oriented control signals. Specifically, communication mechanism, intent, and semantic frame are imported as multi-grained signals that control the empathy realization from coarse to fine levels. We then design a specific masking strategy to reflect the relationship between multi-grained signals and response tokens, and integrate it into the diffusion model to influence the generative process. Experimental results on a benchmark dataset EmpatheticDialogue show that our framework outperforms competitive baselines in terms of controllability, informativeness, and diversity without the loss of context-relatedness.

在这篇论文中，我们提出了一个名为DiffusEmp的框架，它基于条件扩散语言模型，使用显式控制来引导共情表达，并引入了通信机制、意图和语义框架等多粒度信号来控制共情实现。我们设计了一种特定的掩码策略，以反映多粒度信号与响应令牌之间的关系，并将其整合到扩散模型中以影响生成过程。实验结果显示，我们的框架在可控性、信息性和多样性方面优于竞争基线，同时不失去与上下文相关性。

DiffusEmp：一种基于扩散模型的多维度控制框架，用于生成共情式回应