A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding. (arXiv:2211.04023v1 [cs.CL])

Multi-intent detection and slot filling joint models are gaining increasing
traction since they are closer to complicated real-world scenarios. However,
existing approaches (1) focus on identifying implicit correlations between
utterances and one-hot encoded labels in both tasks while ignoring explicit
label characteristics; (2) directly incorporate multi-intent information for
each token, which could lead to incorrect slot prediction due to the
introduction of irrelevant intent. In this paper, we propose a framework termed
DGIF, which first leverages the semantic information of …

arxiv framework graph interactive language semantic spoken language understanding understanding