Profile-based intent detection and slot filling are important tasks aimed at reducing the ambiguity in user utterances by leveraging user-specific supporting profile information. However, research in these two tasks has not been extensively explored. To fill this gap, we propose a joint model, namely JPIS, designed to enhance profile-based intent detection and slot filling. JPIS incorporates the supporting profile information into its encoder and introduces a slot-to-intent attention mechanism to transfer slot information representations to intent detection. Experimental results show that our JPIS substantially outperforms previous profile-based models, establishing a new state-of-the-art performance in overall accuracy on the Chinese benchmark dataset ProSLU.

翻译：基于用户画像的意图检测与槽填充是两项重要任务，旨在通过利用用户特定的辅助画像信息来降低用户话语中的歧义性。然而，目前针对这两项任务的研究尚不充分。为填补这一空白，我们提出了一种名为JPIS的联合模型，旨在增强基于用户画像的意图检测与槽填充性能。JPIS将辅助画像信息融入其编码器，并引入了一种槽到意图注意力机制，用于将槽信息表示传递至意图检测模块。实验结果表明，我们的JPIS模型显著优于现有的基于用户画像的模型，在中文基准数据集ProSLU上实现了总体准确率的最新最佳性能。