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    <titleInfo>
        <title>MalUpama - Figurative Language Identification in Malayalam -An Experimental Study</title>
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    <name type="personal">
        <namePart type="given">Reenu</namePart>
        <namePart type="family">Paul</namePart>
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    <name type="personal">
        <namePart type="given">Wincy</namePart>
        <namePart type="family">Abraham</namePart>
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    <name type="personal">
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        <namePart type="family">S. Pillai</namePart>
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            <title>Proceedings of the 21st International Conference on Natural Language Processing (ICON)</title>
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            <namePart type="given">Sobha</namePart>
            <namePart type="family">Lalitha Devi</namePart>
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            <namePart type="given">Karunesh</namePart>
            <namePart type="family">Arora</namePart>
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    <abstract>Figurative language, particularly in under represented languages within the Dravidian family, serves as a critical medium for conveying emotions and cultural meaning. Despite the rich literary traditions of languages such as Malayalam, Tamil, Telugu, and Kannada, there has been minimal progress in developing computational techniques to analyze figurative expressions. Historically, Malayalam was known by various names, such as Malayanma and Malabari. Similarly Kerala was known as Malanadu before adopting its current name, which metaphorically refers to the land between the Indian Ocean and the Western Ghats. In this study, we introduce the UPAMA Model(MalUpama), designed to identify Similes in Malayalam, an under-resourced Dravidian language mostly spoken in the state of southern India, Kerala. The current research focuses on detection of presence of Simile in Malayalam prose using the ‘Upama model’. This paper outlines the detection of Simile in Malayalam sentences and a detection accuracy of 94.5% is achieved by the proposed method. To the best of our knowledge this is the first work in the Malayalam language, explores computational techniques with a particular focus on applying machine learning to analyze figurative expressions which can be adopted for other Dravidian Languages too. The dataset developed for this study is made publicly available, allowing scholars to contribute and explore more on the category ‘Upama’ of Figurative Languages (‘Alankarangal’) of Malayalam language.</abstract>
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        <date>2024-12</date>
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%0 Conference Proceedings
%T MalUpama - Figurative Language Identification in Malayalam -An Experimental Study
%A Paul, Reenu
%A Abraham, Wincy
%A S. Pillai, Anitha
%Y Lalitha Devi, Sobha
%Y Arora, Karunesh
%S Proceedings of the 21st International Conference on Natural Language Processing (ICON)
%D 2024
%8 December
%I NLP Association of India (NLPAI)
%C AU-KBC Research Centre, Chennai, India
%F paul-etal-2024-malupama
%X Figurative language, particularly in under represented languages within the Dravidian family, serves as a critical medium for conveying emotions and cultural meaning. Despite the rich literary traditions of languages such as Malayalam, Tamil, Telugu, and Kannada, there has been minimal progress in developing computational techniques to analyze figurative expressions. Historically, Malayalam was known by various names, such as Malayanma and Malabari. Similarly Kerala was known as Malanadu before adopting its current name, which metaphorically refers to the land between the Indian Ocean and the Western Ghats. In this study, we introduce the UPAMA Model(MalUpama), designed to identify Similes in Malayalam, an under-resourced Dravidian language mostly spoken in the state of southern India, Kerala. The current research focuses on detection of presence of Simile in Malayalam prose using the ‘Upama model’. This paper outlines the detection of Simile in Malayalam sentences and a detection accuracy of 94.5% is achieved by the proposed method. To the best of our knowledge this is the first work in the Malayalam language, explores computational techniques with a particular focus on applying machine learning to analyze figurative expressions which can be adopted for other Dravidian Languages too. The dataset developed for this study is made publicly available, allowing scholars to contribute and explore more on the category ‘Upama’ of Figurative Languages (‘Alankarangal’) of Malayalam language.
%U https://aclanthology.org/2024.icon-1.41/
%P 357-367

Markdown (Informal)

[MalUpama - Figurative Language Identification in Malayalam -An Experimental Study](https://aclanthology.org/2024.icon-1.41/) (Paul et al., ICON 2024)

• MalUpama - Figurative Language Identification in Malayalam -An Experimental Study (Paul et al., ICON 2024)

ACL

• Reenu Paul, Wincy Abraham, and Anitha S. Pillai. 2024. MalUpama - Figurative Language Identification in Malayalam -An Experimental Study. In Proceedings of the 21st International Conference on Natural Language Processing (ICON), pages 357–367, AU-KBC Research Centre, Chennai, India. NLP Association of India (NLPAI).