CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding

Spoken Language Understanding (SLU) mainly involves two tasks, intent detection and slot filling, which are generally modeled jointly in existing works. However, most existing models fail to fully utilize co-occurrence relations between slots and intents, which restricts their potential performance... (read more)

PDF Abstract IJCNLP 2019 PDF IJCNLP 2019 Abstract

Datasets


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
Memory Network
Working Memory Models