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        <title>Variation and Instability in Dialect-Based Embedding Spaces</title>
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        <namePart type="given">Jonathan</namePart>
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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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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Tommi</namePart>
            <namePart type="family">Jauhiainen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Nikola</namePart>
            <namePart type="family">Ljubešić</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Preslav</namePart>
            <namePart type="family">Nakov</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Jörg</namePart>
            <namePart type="family">Tiedemann</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Marcos</namePart>
            <namePart type="family">Zampieri</namePart>
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    <abstract>This paper measures variation in embedding spaces which have been trained on different regional varieties of English while controlling for instability in the embeddings. While previous work has shown that it is possible to distinguish between similar varieties of a language, this paper experiments with two follow-up questions: First, does the variety represented in the training data systematically influence the resulting embedding space after training? This paper shows that differences in embeddings across varieties are significantly higher than baseline instability. Second, is such dialect-based variation spread equally throughout the lexicon? This paper shows that specific parts of the lexicon are particularly subject to variation. Taken together, these experiments confirm that embedding spaces are significantly influenced by the dialect represented in the training data. This finding implies that there is semantic variation across dialects, in addition to previously-studied lexical and syntactic variation.</abstract>
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    <identifier type="doi">10.18653/v1/2023.vardial-1.7</identifier>
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        <date>2023-05</date>
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            <start>67</start>
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%0 Conference Proceedings
%T Variation and Instability in Dialect-Based Embedding Spaces
%A Dunn, Jonathan
%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 dunn-2023-variation
%X This paper measures variation in embedding spaces which have been trained on different regional varieties of English while controlling for instability in the embeddings. While previous work has shown that it is possible to distinguish between similar varieties of a language, this paper experiments with two follow-up questions: First, does the variety represented in the training data systematically influence the resulting embedding space after training? This paper shows that differences in embeddings across varieties are significantly higher than baseline instability. Second, is such dialect-based variation spread equally throughout the lexicon? This paper shows that specific parts of the lexicon are particularly subject to variation. Taken together, these experiments confirm that embedding spaces are significantly influenced by the dialect represented in the training data. This finding implies that there is semantic variation across dialects, in addition to previously-studied lexical and syntactic variation.
%R 10.18653/v1/2023.vardial-1.7
%U https://aclanthology.org/2023.vardial-1.7
%U https://doi.org/10.18653/v1/2023.vardial-1.7
%P 67-77

Markdown (Informal)

[Variation and Instability in Dialect-Based Embedding Spaces](https://aclanthology.org/2023.vardial-1.7) (Dunn, VarDial 2023)

• Variation and Instability in Dialect-Based Embedding Spaces (Dunn, VarDial 2023)

ACL

• Jonathan Dunn. 2023. Variation and Instability in Dialect-Based Embedding Spaces. In Tenth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2023), pages 67–77, Dubrovnik, Croatia. Association for Computational Linguistics.