基于伪标签和迁移学习的双关语识别方法OA北大核心CSTPCD

To address the problem of shortage of the pun samples,this paper proposes a pun recognition model based on pseudo-label speech-focused context(pun detection based on pseudo-label and transfer learning).Firstly,the model uses contextual semantics,phoneme vector and attention mechanism to generate pseudo-labels.Then,it combines transfer learning and confidence to select useful pseudo-labels.Finally,the pseudo-label data and real data are used for network theory and training,and the pseudo-label labeling and mixed training procedures are repeated.To a certain extent,the problem of small sample size and difficulty in obtaining puns has been solved.By this model,we carry out pun detection experiments on both the SemEval 2017 shared task 7 dataset and the Pun of the Day dataset.The results show that the performance of this model is better than that of the existing mainstream pun recognition methods.