用分层智能体控制叙事情绪波动，实现心理疗愈所需的精准情感表达。
Steering Emotional Dynamics for Art Therapy: Controllable Narrative Script Generation through Hierarchically Guided LLM Agents
- 分三层控制：整体情绪路径规划、角色驱动场景生成、局部情绪精细调节。
- 实验显示在情感轨迹一致性上显著优于基线方法，可控性出色。
- 适合需要情绪引导的AI辅助心理治疗场景，如艺术疗愈与情感表达支持。
艺术疗愈在情绪修复中至关重要，叙事创作是情感表达的核心载体。由于情绪具有动态变化特性，能够精确控制情绪起伏的叙事有助于安全投射内心冲突并实现情绪宣泄。近年来，大型语言模型（LLMs）的发展为自动化叙事生成提供了新路径。然而，现有方法虽能生成流畅文本，却难以遵循指定的情感演变轨迹，无法满足以情绪为导向的心理疗愈需求。为此，本文提出EC-Script——一种基于LLM智能体的框架，实现叙事生成中情感轨迹的层级化控制。通过情绪轨迹规划确定整体叙事方向，角色驱动场景生成推进剧情发展，情绪控制剧本写作调节角色局部情绪变化，最终输出严格符合预设情感轨迹的分幕剧本。实验结果表明，EC-Script在情感轨迹遵循度上显著优于基线方法，展现出优异且可靠的可控性，为人工智能辅助情绪疗愈提供了有效技术支撑。
原文摘要 · Abstract (English)
Art therapy plays a vital role in emotional healing, in which narrative creation acts as the primary vehicle for emotional expression. Given the inherently dynamic nature of emotions during healing, narratives with finely controlled emotional fluctuations enable individuals to safely project inner conflicts and achieve emotional catharsis. Recently, with the rapid development of Large Language Models (LLMs), automated narrative generation technology has provided a new pathway to support such artistic designs. However, while existing methods can produce fluent texts, they struggle to generate narratives that adhere to specified affective trajectories, failing to meet the demands of emotion-oriented psychological healing. To address these issues, this paper proposes EC-Script, an LLM agent-based framework that enables hierarchical control of the affective trajectory in narrative generation for emotional healing. To ensure that the generated narratives strictly follow the given emotional patterns, EC-Script establishes overall narrative direction through Emotion-Trajectory Planning, propels scene-level plot development with Character-Driven Scene Generation, and regulates local emotional changes of characters via Emotion-Controlled Script Writing. Ultimately, it outputs scene-by-scene script content that remains highly consistent with the preset affective trajectory. Experimental results demonstrate that EC-Script significantly outperforms baseline methods in affective trajectory adherence, exhibiting excellent and reliable emotional controllability, thereby providing effective technical support for AI-assisted emotional healing scenarios.
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