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35 - Natural Language Processing

from Part 6 - Experimental and Quantitative Approaches

Published online by Cambridge University Press:  16 May 2024

By
Tomaž Erjavec
Edited by
Danko Šipka  and
Wayles Browne
Danko Šipka
Affiliation:
Arizona State University
Wayles Browne
Affiliation:
Cornell University, New York
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Summary

This chapter surveys the history and main directions of natural language processing research in general, and for Slavic languages in particular. The field has grown enormously since its beginning. Especially since 2010, the amount of digital texts has been rapidly growing; furthermore, research has yielded an ever-greater number of highly usable applications. This is reflected in the increasing number and attendance of NLP conferences and workshops. Slavic countries are no exception; several have been organising international conferences for decades, and their proceedings are the best place to find publications on Slavic NLP research. The general trend of the evolution of NLP is difficult to predict. It is certain that deep learning, including various new types (e.g. contextual, multilingual) of word embeddings and similar ‘deep’ models will play an increasing role, while predictions also mention the increasing importance of the Universal Dependencies framework and treebanks and research into the theory, not only the practice, of deep learning, coupled with attempts at achieving better explainability of the resulting models.

Keywords

computational linguisticscorpus linguisticsnatural language processinglanguage resourcestaggersparsers
Type
Chapter
Information
The Cambridge Handbook of Slavic Linguistics , pp. 732 - 750
Publisher: Cambridge University Press
Print publication year: 2024

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