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Why Can Computers Understand Natural Language?: The Structuralist Image of Language Behind Word Embeddings

Philosophy & technology, 2021-03, Vol.34 (1), p.149-214 [Peer Reviewed Journal]

Springer Nature B.V. 2020 ;Attribution ;ISSN: 2210-5433 ;EISSN: 2210-5441 ;DOI: 10.1007/s13347-020-00393-9

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  • Title:
    Why Can Computers Understand Natural Language?: The Structuralist Image of Language Behind Word Embeddings
  • Author: Gastaldi, Juan Luis
  • Subjects: Artificial Intelligence ; Cognitive science ; Computation and Language ; Computer Science ; Computers and Society ; Education ; History, Philosophy and Sociology of Sciences ; Humanities and Social Sciences ; Linguistics ; Methods and statistics ; Philosophy ; Philosophy of Technology ; Research Article
  • Is Part Of: Philosophy & technology, 2021-03, Vol.34 (1), p.149-214
  • Description: The present paper intends to draw the conception of language implied in the technique of word embeddings that supported the recent development of deep neural network models in computational linguistics. After a preliminary presentation of the basic functioning of elementary artificial neural networks, we introduce the motivations and capabilities of word embeddings through one of its pioneering models, word2vec. To assess the remarkable results of the latter, we inspect the nature of its underlying mechanisms, which have been characterized as the implicit factorization of a word-context matrix. We then discuss the ordinary association of the “distributional hypothesis” with a “use theory of meaning,” often justifying the theoretical basis of word embeddings, and contrast them to the theory of meaning stemming from those mechanisms through the lens of matrix models (such as vector space models and distributional semantic models). Finally, we trace back the principles of their possible consistency through Harris’s original distributionalism up to the structuralist conception of language of Saussure and Hjelmslev. Other than giving access to the technical literature and state of the art in the field of natural language processing to non-specialist readers, the paper seeks to reveal the conceptual and philosophical stakes involved in the recent application of new neural network techniques to the computational treatment of language.
  • Publisher: Dordrecht: Springer Netherlands
  • Language: English
  • Identifier: ISSN: 2210-5433
    EISSN: 2210-5441
    DOI: 10.1007/s13347-020-00393-9
  • Source: HAL SHS: Archive ouverte en Sciences de l'Homme et de la Société (Open Access)
    Hyper Article en Ligne (HAL) (Open Access)
    ProQuest Central
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