关键词: 意图识别, 口语理解, 对话系统, 人工智能

Abstract: Spoken Language Understanding（SLU） is a vital part of the human-machine dialogue system, which includes an important sub-task called intent detection. The accuracy of intent detection is directly related to the performance of semantic slot filling, and it is helpful to the following research of the dialogue system. Considering the difficulty of intent detection in human-machine dialogue system, the traditional machine learning methods cannot understand the deep semantic information of user’s discourse. This paper mainly analyzes, compares and summarizes the deep learning methods applied in the research of intent detection in recent years, and further considers how to apply deep learning model to multi-intent detection task, so as to promote the research of multi-intent detection methods based on deep neural network.

Key words: intent detection, Spoken Language Understanding（SLU）, dialogue system, artificial intelligence