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位填充是通过利用用户特定的支持性画像信息来减少用户话语歧义的重要任务。然而，这两个任务的研究尚未得到广泛探索。为填补这一空白，我们提出了一种联合模型JPIS，旨在增强基于用户画像的意图检测与槽位填充。JPIS将支持性画像信息融入其编码器，并引入了一种槽位到意图注意力机制，将槽位信息表示传输至意图检测。实验结果表明，我们的JPIS显著优于先前的基于用户画像的模型，在中文基准数据集ProSLU上实现了整体准确率的最新最佳性能。