Exploiting domain-slot related keywords description for Few-Shot Cross-Domain Dialogue State Tracking
Gao Qixiang, Guanting Dong, Yutao Mou, Liwen Wang, Chen Zeng, Daichi Guo, Mingyang Sun, Weiran Xu · 2022
Collecting dialogue data with domain-slotvalue labels for dialogue state tracking (DST) could be a costly process.In this paper, we propose a novel framework based on domain-slot related description to tackle the challenge of few-shot cross-domain DST.Specifically, we design an extraction module to extract domainslot related verbs and nouns in the dialogue.Then, we integrates them into the description, which aims to prompt the model to identify the slot information.Furthermore, we introduce a random sampling strategy to improve the domain generalization ability of the model.We utilize a pre-trained model to encode contexts and description and generates answers with an auto-regressive manner.Experimental results show that our approaches substantially outperform the existing few-shot DST methods on MultiWOZ and gain strong improvements on the slot accuracy comparing to existing slot description methods.