@inproceedings{thaniserikaran-harikrishnan-2026-phonetic,
    title = "Phonetic Cues Improve {LLM}-Based Pun Detection in Short Text",
    author = "Thaniserikaran, Adith Santosh  and
      Harikrishnan, Govind",
    editor = "Amir, Ori  and
      Hempelmann, Christian F.  and
      Rayz, Julia  and
      Dong, Tiansi  and
      Miller, Tristan",
    booktitle = "Proceedings of the 2nd Workshop on Computational Humor ({CH}um 2026)",
    month = jul,
    year = "2026",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.chum-1.6/",
    pages = "72--80",
    ISBN = "979-8-89176-431-6",
    abstract = "This paper studies joke detection in short text, focusing only on jokes triggered by lexical ambiguity. Following Attardo and Raskin, we treat these jokes as cases where humor arises from a script opposition activated through a logical mechanism such as homography or homophony. Our framework combines contextuals emantic analysis for homographs with phoneme-level similarity for homophones and near-homophones, using CMUdict, weighted Levenshtein distance, and prompt-based reasoning to recover ambiguities that are not visible in spelling alone. Results show that explicit phonetic modeling improves detection of sound-based puns."
}