Semantic Slot Filling Based on BERT and BiLSTM

BERT is used for intent recognition and slot filling because it effectively integrates the semantic information of intention and slot labels

For intent detection and slot filling, the use of BERT has also brought about a significant effect improvement in joint models However, although

bert for joint intent classification and slot filling BERT with external slot se- quence as 2nd sequence 77 Table 2: Comparison of BERT model We believe the pipeline approach to such user-developed

live slot game While non-categorical slots are classified by detecting relevant spans in the dialogue, categorical slots use a fixed BERT model to encode all