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        <title>Letters From the Past: Modeling Historical Sound Change Through Diachronic Character Embeddings</title>
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            <namePart type="given">Preslav</namePart>
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    <abstract>While a great deal of work has been done on NLP approaches to lexical semantic change detection, other aspects of language change have received less attention from the NLP community. In this paper, we address the detection of sound change through historical spelling. We propose that a sound change can be captured by comparing the relative distance through time between the distributions of the characters involved before and after the change has taken place. We model these distributions using PPMI character embeddings. We verify this hypothesis in synthetic data and then test the method’s ability to trace the well-known historical change of lenition of plosives in Danish historical sources. We show that the models are able to identify several of the changes under consideration and to uncover meaningful contexts in which they appeared. The methodology has the potential to contribute to the study of open questions such as the relative chronology of sound shifts and their geographical distribution.</abstract>
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    <identifier type="doi">10.18653/v1/2022.acl-long.463</identifier>
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%0 Conference Proceedings
%T Letters From the Past: Modeling Historical Sound Change Through Diachronic Character Embeddings
%A Boldsen, Sidsel
%A Paggio, Patrizia
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F boldsen-paggio-2022-letters
%X While a great deal of work has been done on NLP approaches to lexical semantic change detection, other aspects of language change have received less attention from the NLP community. In this paper, we address the detection of sound change through historical spelling. We propose that a sound change can be captured by comparing the relative distance through time between the distributions of the characters involved before and after the change has taken place. We model these distributions using PPMI character embeddings. We verify this hypothesis in synthetic data and then test the method’s ability to trace the well-known historical change of lenition of plosives in Danish historical sources. We show that the models are able to identify several of the changes under consideration and to uncover meaningful contexts in which they appeared. The methodology has the potential to contribute to the study of open questions such as the relative chronology of sound shifts and their geographical distribution.
%R 10.18653/v1/2022.acl-long.463
%U https://aclanthology.org/2022.acl-long.463
%U https://doi.org/10.18653/v1/2022.acl-long.463
%P 6713-6722

Markdown (Informal)

[Letters From the Past: Modeling Historical Sound Change Through Diachronic Character Embeddings](https://aclanthology.org/2022.acl-long.463) (Boldsen & Paggio, ACL 2022)

• Letters From the Past: Modeling Historical Sound Change Through Diachronic Character Embeddings (Boldsen & Paggio, ACL 2022)

ACL

• Sidsel Boldsen and Patrizia Paggio. 2022. Letters From the Past: Modeling Historical Sound Change Through Diachronic Character Embeddings. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 6713–6722, Dublin, Ireland. Association for Computational Linguistics.