重庆大学学报2024，Vol.47Issue(2)：51-61,11.DOI:10.11835/j.issn.1000.582X.2024.02.006
基于伪标签和迁移学习的双关语识别方法
Pun detection basd on pseudo-label and transfer learning
摘要
Abstract
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.关键词
双关语检测/伪标签/迁移学习Key words
pun detection/pseudo-label/transfer learning分类
信息技术与安全科学引用本文复制引用
姜思羽,张智恒,姜立标,马乐,陈博远,王连喜,赵亮..基于伪标签和迁移学习的双关语识别方法[J].重庆大学学报,2024,47(2):51-61,11.基金项目
广州市科技计划资助项目(202102020637,202002030227) （202102020637,202002030227）
广东外语外贸大学师生合作资助项目(21SS10).Supported by Guangzhou Science and Technology Plan Project(202102020637,202002030227)and Teacher-Student Joint Research Project on Guangdong University of Foreign Studies(21SS10). （21SS10）
