A survey of joint intent detection and slot filling models in natural language understanding

Henry Weld, Xiaoqi Huang, Siqu Long, Josiah Poon, Soyeon Caren Han
2022 ACM Computing Surveys  
Intent classification, to identify the speaker's intention, and slot filling, to label each token with a semantic type, are critical tasks in natural language understanding. Traditionally the two tasks have been addressed independently. More recently joint models, that address the two tasks together, have achieved state-of-the-art performance for each task, and have shown there exists a strong relationship between the two. In this survey we bring the coverage of methods up to 2021 including the
more » ... many applications of deep learning in the field. As well as a technological survey we look at issues addressed in the joint task, and the approaches designed to address these issues. We cover data sets, evaluation metrics, experiment design and supply a summary of reported performance on the standard data sets.
doi:10.1145/3547138 fatcat:sbv2bqasqba6zkojqmi4jb4blm