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        <title>Two-stage Pipeline for Multilingual Dialect Detection</title>
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            <title>Tenth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2023)</title>
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        <name type="personal">
            <namePart type="given">Yves</namePart>
            <namePart type="family">Scherrer</namePart>
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        <name type="personal">
            <namePart type="given">Tommi</namePart>
            <namePart type="family">Jauhiainen</namePart>
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        <name type="personal">
            <namePart type="given">Nikola</namePart>
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            <namePart type="given">Preslav</namePart>
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            <namePart type="family">Tiedemann</namePart>
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    <abstract>Dialect Identification is a crucial task for localizing various Large Language Models. This paper outlines our approach to the VarDial 2023 shared task. Here we have to identify three or two dialects from three languages each which results in a 9-way classification for Track-1 and 6-way classification for Track-2 respectively. Our proposed approach consists of a two-stage system and outperforms other participants’ systems and previous works in this domain. We achieve a score of 58.54% for Track-1 and 85.61% for Track-2. Our codebase is available publicly (https://github.com/ankit-vaidya19/EACL_VarDial2023).</abstract>
    <identifier type="citekey">vaidya-kane-2023-two</identifier>
    <identifier type="doi">10.18653/v1/2023.vardial-1.22</identifier>
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            <start>222</start>
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%0 Conference Proceedings
%T Two-stage Pipeline for Multilingual Dialect Detection
%A Vaidya, Ankit
%A Kane, Aditya
%Y Scherrer, Yves
%Y Jauhiainen, Tommi
%Y Ljubešić, Nikola
%Y Nakov, Preslav
%Y Tiedemann, Jörg
%Y Zampieri, Marcos
%S Tenth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2023)
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F vaidya-kane-2023-two
%X Dialect Identification is a crucial task for localizing various Large Language Models. This paper outlines our approach to the VarDial 2023 shared task. Here we have to identify three or two dialects from three languages each which results in a 9-way classification for Track-1 and 6-way classification for Track-2 respectively. Our proposed approach consists of a two-stage system and outperforms other participants’ systems and previous works in this domain. We achieve a score of 58.54% for Track-1 and 85.61% for Track-2. Our codebase is available publicly (https://github.com/ankit-vaidya19/EACL_VarDial2023).
%R 10.18653/v1/2023.vardial-1.22
%U https://aclanthology.org/2023.vardial-1.22
%U https://doi.org/10.18653/v1/2023.vardial-1.22
%P 222-229

Markdown (Informal)

[Two-stage Pipeline for Multilingual Dialect Detection](https://aclanthology.org/2023.vardial-1.22) (Vaidya & Kane, VarDial 2023)

• Two-stage Pipeline for Multilingual Dialect Detection (Vaidya & Kane, VarDial 2023)

ACL

• Ankit Vaidya and Aditya Kane. 2023. Two-stage Pipeline for Multilingual Dialect Detection. In Tenth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2023), pages 222–229, Dubrovnik, Croatia. Association for Computational Linguistics.