Bi-directional Joint Model for Intent Detection and Slot Filling

doi:10.1109/ICAACE61206.2024.10549248

	Bi-directional Joint Model for Intent Detection and Slot Filling
	Luo, Bin; Feng, Baiming
	2024
会议名称	7th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2024
会议录名称	2024 7th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2024
页码	1311-1314
会议日期	March 1, 2024 - March 3, 2024
会议地点	Hybrid, Shanghai, China
会议录编者/会议主办者	IEEE
出版者	Institute of Electrical and Electronics Engineers Inc.
摘要	Natural language understanding plays a very important role in textual information processing systems, and is a necessary module for systems such as recommendation, question and answer, and search. Intent detection and slot filling are two crucial tasks for natural language understanding. Traditionally the two tasks were proceeded independently. Recently some studies have shown that the two tasks are correlative strongly, and some joint models have achieved better performance. However, they still have difficulty in capturing the mutual information between the two tasks adequately. To address the underutilization of mutual information in the above two tasks, this papers proposes a new bi-directional joint model for intent detection and slot filling, which contains an input embedding layer, a slot enhancement layer and an intent enhancement layer, where the input embedding layer uses BERT as the underlying encoder, the slot enhancement layer is to add the intent information of the whole sentence as a guideline to establish a deeper connection between the slot and the intent in the process of slot filling, and the intent enhancement layer is similar. Experimental results on Snips dataset demonstrate that our model achieves state-of-the-art results in slot F1(97.1%) and sentence-level semantic frame accuracy(93.1%), indicating that our model is able to capture the mutual information between the semantic components in the NLU tasks more adequately. © 2024 IEEE.
关键词	Embeddings Search engines Semantics BERT Bi-directional joints Component Embeddings Enhancement Layers Intent detection Joint models Mutual informations Natural language understanding Slot filling
DOI	10.1109/ICAACE61206.2024.10549248
收录类别	EI
语种	英语
EI入藏号	20242716656312
EI主题词	Filling
EI分类号	691.2 Materials Handling Methods ; 723 Computer Software, Data Handling and Applications ; 723.4 Artificial Intelligence
原始文献类型	Conference article (CA)
文献类型	会议论文
条目标识符	https://ir.nwnu.edu.cn/handle/39RV6HYL/98801
专题	实体学院_计算机科学与工程学院
作者单位	College Of Computer Science And Engineering, Northwest Normal University, Gansu, Lanzhou, China
第一作者单位	计算机科学与工程学院
第一作者的第一单位	计算机科学与工程学院
推荐引用方式 GB/T 7714	Luo, Bin,Feng, Baiming. Bi-directional Joint Model for Intent Detection and Slot Filling[C]//IEEE:Institute of Electrical and Electronics Engineers Inc.,2024:1311-1314.