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        <title>CUFE@NLU of Devanagari Script Languages 2025: Language Identification using fastText</title>
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            <namePart type="given">Kengatharaiyer</namePart>
            <namePart type="family">Sarveswaran</namePart>
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        <name type="personal">
            <namePart type="given">Ashwini</namePart>
            <namePart type="family">Vaidya</namePart>
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        <name type="personal">
            <namePart type="given">Bal</namePart>
            <namePart type="family">Krishna Bal</namePart>
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            <namePart type="given">Sana</namePart>
            <namePart type="family">Shams</namePart>
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        <name type="personal">
            <namePart type="given">Surendrabikram</namePart>
            <namePart type="family">Thapa</namePart>
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            <publisher>International Committee on Computational Linguistics</publisher>
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    <abstract>Language identification is a critical area of research within natural language processing (NLP), particularly in multilingual contexts where accurate language detection can enhance the performance of various applications, such as machine translation, content moderation, and user interaction systems. This paper presents a language identification system developed using fastText. In the CHIPSAL@COLING 2025 Task on Devanagari Script Language Identification, the proposed method achieved first place, with an F1 score of 0.9997.</abstract>
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%0 Conference Proceedings
%T CUFE@NLU of Devanagari Script Languages 2025: Language Identification using fastText
%A Ibrahim, Michael
%Y Sarveswaran, Kengatharaiyer
%Y Vaidya, Ashwini
%Y Krishna Bal, Bal
%Y Shams, Sana
%Y Thapa, Surendrabikram
%S Proceedings of the First Workshop on Challenges in Processing South Asian Languages (CHiPSAL 2025)
%D 2025
%8 January
%I International Committee on Computational Linguistics
%C Abu Dhabi, UAE
%F ibrahim-2025-cufe-nlu
%X Language identification is a critical area of research within natural language processing (NLP), particularly in multilingual contexts where accurate language detection can enhance the performance of various applications, such as machine translation, content moderation, and user interaction systems. This paper presents a language identification system developed using fastText. In the CHIPSAL@COLING 2025 Task on Devanagari Script Language Identification, the proposed method achieved first place, with an F1 score of 0.9997.
%U https://aclanthology.org/2025.chipsal-1.30/
%P 273-277

Markdown (Informal)

[CUFE@NLU of Devanagari Script Languages 2025: Language Identification using fastText](https://aclanthology.org/2025.chipsal-1.30/) (Ibrahim, CHiPSAL 2025)

• CUFE@NLU of Devanagari Script Languages 2025: Language Identification using fastText (Ibrahim, CHiPSAL 2025)

ACL

• Michael Ibrahim. 2025. CUFE@NLU of Devanagari Script Languages 2025: Language Identification using fastText. In Proceedings of the First Workshop on Challenges in Processing South Asian Languages (CHiPSAL 2025), pages 273–277, Abu Dhabi, UAE. International Committee on Computational Linguistics.