基于多粒度语义交互理解网络的幽默等级识别(A Multi-Granularity Semantic Interaction Understanding Network for Humor Level Recognition)
Jinhui Zhang (张瑾晖), Shaowu Zhang (张绍武), Xiaochao Fan (樊小超), Liang Yang (杨亮), Hongfei Lin (林鸿飞)
Abstract
幽默在人们日常交流中发挥着重要作用。随着人工智能的快速发展,幽默等级识别成为自然语言处理领域的热点研究问题之一。已有的幽默等级识别研究往往将幽默文本看作一个整体,忽视了幽默文本内部的语义关系。本文将幽默等级识别视为自然语言推理任务,将幽默文本划分为“铺垫”和“笑点”两个部分,分别对其语义和语义关系进行建模,提出了一种多粒度语义交互理解网络,从单词和子句两个粒度捕获幽默文本中语义的关联和交互。本文在Reddit公开幽默数据集上进行了实验,相比之前最优结果,模型在语料上的准确率提升了1.3%。实验表明,引入幽默内部的语义关系信息可以提高模型幽默识别的性能,而本文提出的模型也可以很好地建模这种语义关系。- Anthology ID:
- 2020.ccl-1.60
- Volume:
- Proceedings of the 19th Chinese National Conference on Computational Linguistics
- Month:
- October
- Year:
- 2020
- Address:
- Haikou, China
- Venue:
- CCL
- SIG:
- Publisher:
- Chinese Information Processing Society of China
- Note:
- Pages:
- 645–655
- Language:
- Chinese
- URL:
- https://aclanthology.org/2020.ccl-1.60
- DOI:
- Cite (ACL):
- Jinhui Zhang, Shaowu Zhang, Xiaochao Fan, Liang Yang, and Hongfei Lin. 2020. 基于多粒度语义交互理解网络的幽默等级识别(A Multi-Granularity Semantic Interaction Understanding Network for Humor Level Recognition). In Proceedings of the 19th Chinese National Conference on Computational Linguistics, pages 645–655, Haikou, China. Chinese Information Processing Society of China.
- Cite (Informal):
- 基于多粒度语义交互理解网络的幽默等级识别(A Multi-Granularity Semantic Interaction Understanding Network for Humor Level Recognition) (Zhang et al., CCL 2020)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2020.ccl-1.60.pdf