Division and the Digital Language Divide: A Critical Perspective on Natural Language Processing Resources for the South and North Korean Languages.

The digital world is marked by large asymmetries in the volume of content available between different languages. As a direct corollary, this inequality also exists, amplified, in the number of resources (labeled and unlabeled datasets, pretrained models, academic research) available for the computat...

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Publicado en:Korean Studies Vol. 47; pp. 243 - 274
Autor principal: Berthelier, Benoit
Formato: Artículo
Publicado: University of Hawai'i 2023
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Acceso en línea:Ver este registro en EBSCOhost
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        atl: Division and the Digital Language Divide: A Critical Perspective on Natural Language Processing Resources for the South and North Korean Languages.
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        au: Berthelier, Benoit
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        Natural language processing
        Korean language
        Language models
        Computational linguistics
        Digital divide
        Sociolinguistics
        Linguistic rights
        North Korea
        South Korea
      sug:
        subj:
          North Korea
          South Korea
          Natural language processing
          Korean language
          Language models
          Computational linguistics
          Digital divide
          Sociolinguistics
          Linguistic rights
      keyword:
        artificial intelligence
        ideology
        large language models
        natural language processing
      ab: The digital world is marked by large asymmetries in the volume of content available between different languages. As a direct corollary, this inequality also exists, amplified, in the number of resources (labeled and unlabeled datasets, pretrained models, academic research) available for the computational analysis of these languages or what is generally called natural language processing (NLP). NLP literature divides languages between high- and low-resource languages. Thanks to early private and public investment in the field, the Korean language is generally considered to be a high-resource language. Yet, the good fortunes of Korean in the age of machine learning obscure the divided state of the language, as recensions of available resources and research solely focus on the standard language of South Korea, thus making it the sole representant of an otherwise diverse linguistic family that includes the Northern standard language as well as regional and diasporic dialects. This paper shows that the resources developed for the South Korean language do not necessarily transfer to the North Korean language. However, it also argues that this does not make North Korean a low-resource language. On one hand, South Korean resources can be augmented with North Korean data to achieve better performance. On the other, North Korean has more resources than commonly assumed. Retracing the long history of NLP research in North Korea, the paper shows that a large number of datasets and research exists for the North Korean language even if they are not easily available. The paper concludes by exploring the possibility of "unified" language models and underscoring the need for active NLP research collaboration across the Korean peninsula.
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