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A survey of joint intent detection and slot filling models in natural language understanding
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
doi:10.1145/3547138
fatcat:sbv2bqasqba6zkojqmi4jb4blm