<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="asapu-etal-2025-bridging">
    <titleInfo>
        <title>Bridging Laughter Across Languages: Generation of Hindi-English Code-mixed Puns</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Likhith</namePart>
        <namePart type="family">Asapu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Prashant</namePart>
        <namePart type="family">Kodali</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ashna</namePart>
        <namePart type="family">Dua</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kapil</namePart>
        <namePart type="family">Rajesh Kavitha</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Manish</namePart>
        <namePart type="family">Shrivastava</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2025-01</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 1st Workshop on Computational Humor (CHum)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Christian</namePart>
            <namePart type="given">F</namePart>
            <namePart type="family">Hempelmann</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Julia</namePart>
            <namePart type="family">Rayz</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Tiansi</namePart>
            <namePart type="family">Dong</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Tristan</namePart>
            <namePart type="family">Miller</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Puns, as a linguistic phenomenon, hold significant importance in both humor and language comprehension. While extensive research has been conducted in the realm of pun generation in English, there exists a notable gap in the exploration of pun generation within code-mixed text, particularly in Hindi-English code-mixed text. This study addresses this gap by offering a computational method specifically designed to create puns in Hindi-English code-mixed text. In our investigation, we delve into three distinct methodologies aimed at pun generation utilizing pun-alternate word pairs. Furthermore, this novel dataset, HECoP, comprising of 2000 human-annotated sentences serves as a foundational resource for training diverse pun detection models. Additionally, we developed a structured pun generation pipeline capable of generating puns from a single input word without relying on predefined word pairs. Through rigorous human evaluations, our study demonstrates the efficacy of our proposed models in generating code-mixed puns. The findings presented herein lay a solid groundwork for future endeavours in pun generation and computational humor within diverse linguistic contexts.</abstract>
    <identifier type="citekey">asapu-etal-2025-bridging</identifier>
    <location>
        <url>https://aclanthology.org/2025.chum-1.5/</url>
    </location>
    <part>
        <date>2025-01</date>
        <extent unit="page">
            <start>32</start>
            <end>57</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Bridging Laughter Across Languages: Generation of Hindi-English Code-mixed Puns
%A Asapu, Likhith
%A Kodali, Prashant
%A Dua, Ashna
%A Rajesh Kavitha, Kapil
%A Shrivastava, Manish
%Y Hempelmann, Christian F.
%Y Rayz, Julia
%Y Dong, Tiansi
%Y Miller, Tristan
%S Proceedings of the 1st Workshop on Computational Humor (CHum)
%D 2025
%8 January
%I Association for Computational Linguistics
%C Online
%F asapu-etal-2025-bridging
%X Puns, as a linguistic phenomenon, hold significant importance in both humor and language comprehension. While extensive research has been conducted in the realm of pun generation in English, there exists a notable gap in the exploration of pun generation within code-mixed text, particularly in Hindi-English code-mixed text. This study addresses this gap by offering a computational method specifically designed to create puns in Hindi-English code-mixed text. In our investigation, we delve into three distinct methodologies aimed at pun generation utilizing pun-alternate word pairs. Furthermore, this novel dataset, HECoP, comprising of 2000 human-annotated sentences serves as a foundational resource for training diverse pun detection models. Additionally, we developed a structured pun generation pipeline capable of generating puns from a single input word without relying on predefined word pairs. Through rigorous human evaluations, our study demonstrates the efficacy of our proposed models in generating code-mixed puns. The findings presented herein lay a solid groundwork for future endeavours in pun generation and computational humor within diverse linguistic contexts.
%U https://aclanthology.org/2025.chum-1.5/
%P 32-57

Markdown (Informal)

[Bridging Laughter Across Languages: Generation of Hindi-English Code-mixed Puns](https://aclanthology.org/2025.chum-1.5/) (Asapu et al., chum 2025)

• Bridging Laughter Across Languages: Generation of Hindi-English Code-mixed Puns (Asapu et al., chum 2025)

ACL

• Likhith Asapu, Prashant Kodali, Ashna Dua, Kapil Rajesh Kavitha, and Manish Shrivastava. 2025. Bridging Laughter Across Languages: Generation of Hindi-English Code-mixed Puns. In Proceedings of the 1st Workshop on Computational Humor (CHum), pages 32–57, Online. Association for Computational Linguistics.