Abstract
The recognition and tagging of special words in English corpus can effectively improve students' learning efficiency. Based on BiLSTM model and CRF model, a BiLSTM-CRF model model is constructed to recognize and automatically label special words in English corpus. The results show that the average accuracy of BiLSTM-CRF model is 95.35% and the average recall rate is 94.83%, which are much higher than other models. We can know from the above that BiLSTM-CRF model can label English professional corpora well and is a practical method.
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