“The Boating Store Had Its Best Sail Ever”: Pronunciation-attentive Contextualized Pun Recognition

Yichao Zhou, Jyun-Yu Jiang, Jieyu Zhao, Kai-Wei Chang, Wei Wang


Abstract
Humor plays an important role in human languages and it is essential to model humor when building intelligence systems. Among different forms of humor, puns perform wordplay for humorous effects by employing words with double entendre and high phonetic similarity. However, identifying and modeling puns are challenging as puns usually involved implicit semantic or phonological tricks. In this paper, we propose Pronunciation-attentive Contextualized Pun Recognition (PCPR) to perceive human humor, detect if a sentence contains puns and locate them in the sentence. PCPR derives contextualized representation for each word in a sentence by capturing the association between the surrounding context and its corresponding phonetic symbols. Extensive experiments are conducted on two benchmark datasets. Results demonstrate that the proposed approach significantly outperforms the state-of-the-art methods in pun detection and location tasks. In-depth analyses verify the effectiveness and robustness of PCPR.
Anthology ID:
2020.acl-main.75
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
813–822
Language:
URL:
https://aclanthology.org/2020.acl-main.75
DOI:
10.18653/v1/2020.acl-main.75
Bibkey:
Cite (ACL):
Yichao Zhou, Jyun-Yu Jiang, Jieyu Zhao, Kai-Wei Chang, and Wei Wang. 2020. “The Boating Store Had Its Best Sail Ever”: Pronunciation-attentive Contextualized Pun Recognition. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 813–822, Online. Association for Computational Linguistics.
Cite (Informal):
“The Boating Store Had Its Best Sail Ever”: Pronunciation-attentive Contextualized Pun Recognition (Zhou et al., ACL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.75.pdf
Video:
 http://slideslive.com/38928896