关键词: 语义槽填充, 意图识别, 联合识别, 深度神经网络

Abstract: Spoken Language Understanding（SLU）, which includes two key sub-tasks slot filling and intent detection, is an important function module of the dialogue system. In recent years, joint recognition methods to solve slot filling and intent detection have become the mainstream methods of SLU. This paper introduces the methods of two sub-tasks, which develop from independent modeling to joint modeling. It focuses on the joint modeling methods based on deep neural network, analyzes current problems and future development trend of two sub-tasks.

Key words: slot filling, intent detection, joint recognition, deep neural network