"The Boating Store Had Its Best Sail Ever": Pronunciation-attentive Contextualized Pun Recognition
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Abstract (arXiv)
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.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Apr 2020.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 0; 2024: 2; 2025: 0; 2026: 4.
9 papers.
- 2022ExPUNations: Augmenting Puns with Keywords and Explanationscited by 21
- 2024"A good pun is its own reword": Can Large Language Models Understand Puns?cited by 21
- 2024Creating a Lens of Chinese Culture: A Multimodal Dataset for Chinese Pun Rebus Art Understandingcited by 11
- 2026On the Wings of Imagination: Conflicting Script-based Multi-role Framework for Humor Caption Generationcited by 3
- 2021Humor@IITK at SemEval-2021 Task 7: Large Language Models for Quantifying Humor and Offensivenesscited by 1
- 2026Words at Play: Benchmarking Audio Pun Understanding in Large Audio-Language Modelscited by 1
- 2026"I See What You Did There": Can Large Vision-Language Models Understand Multimodal Puns?cited by 1
- 2021A Dual-Attention Neural Network for Pun Location and Using Pun-Gloss Pairs for Interpretationcited by 0
- 2026Phun-Bench: Evaluating LLMs on Phonological Understanding in Chinesecited by 0
- 2026Phun-Bench: Evaluating LLMs on Phonological Understanding in Chinese5 Jun 2026
- 2026"I See What You Did There": Can Large Vision-Language Models Understand Multimodal Puns?7 Apr 2026
- 2026Words at Play: Benchmarking Audio Pun Understanding in Large Audio-Language Models19 Mar 2026
- 2026On the Wings of Imagination: Conflicting Script-based Multi-role Framework for Humor Caption Generation6 Feb 2026
- 2024Creating a Lens of Chinese Culture: A Multimodal Dataset for Chinese Pun Rebus Art Understanding14 Jun 2024
- 2024"A good pun is its own reword": Can Large Language Models Understand Puns?21 Apr 2024
- 2022ExPUNations: Augmenting Puns with Keywords and Explanations24 Oct 2022
- 2021A Dual-Attention Neural Network for Pun Location and Using Pun-Gloss Pairs for Interpretation14 Oct 2021
- 2021Humor@IITK at SemEval-2021 Task 7: Large Language Models for Quantifying Humor and Offensiveness2 Apr 2021