Intent Detection and Slot Filling - NLP-progress

bert slot   Dan bert for joint intent classification and slot filling

This section details our proposed method, mcBERT First, we introduce the overall process of our BERT-based slot filling model, which operates under

Natural language understanding has two core tasks: intent classification and slot filling The success of pre-training language models The model employs pre-trained BERT to extract semantic features and utilizes semantic fusion to associate and integrate this information The

bäckaskog slot BERT is used for intent recognition and slot filling because it effectively integrates the semantic information of intention and slot labels The pre-trained model BERT and BiLSTM networks were trained as a wholein order to improve the performance of semantic slot filling