AI-Powered Language Tools and Their Influence on Modern Linguistics

  • Authors

    • Dr. Silvia Diallo School of Multidisciplinary Studies, River State university, Nigeria. Author
    • Dr. Chinedu Eze School of Multidisciplinary Studies, River State university, Nigeria. Author

    DOI:

    https://doi.org/10.67228/3071561X/IJIRHT-2018PI3X8Q

    Published 01-03-2018

  • Artificial Intelligence, Computational Linguistics, Natural Language Processing, Language Technology, Machine Learning, Linguistic Analysis

    Issue

    Vol. 1 No. 1 (2018)

    Section

    Articles

    How to Cite

    [1]
    S. Diallo and C. Eze, “AI-Powered Language Tools and Their Influence on Modern Linguistics”, IJIRHT, vol. 1, no. 1, pp. 01–13, Jan. 2018, doi: 10.67228/3071561X/IJIRHT-2018PI3X8Q.

  • Abstract

    The high rate of development of artificially intelligence (AI) has significantly transformed the linguistic profession by introducing the use of AI-based language applications. Machine learning, deep learning, and natural language processing (NLP) are the driving forces of these tools redefining the methods of how language is studied, generated, and maintained. Since automated translation and speech recognition systems, AI systems are now at the center of linguistic studies and applications of language in practice. In the given article, we derive detailed research on how AI-based language tools impact the contemporary linguistics. It explores theoretical and historical developments, methodological and practical changes within the subdomains of linguistics. A systematic review of the literature brings out main milestones, trends in the research, and shortcomings of the available methods. The suggested methodology is going to assess AI-based linguistic tools based on both qualitative and quantitative scales, such as accuracy, linguistic validity, scalability, and interpretability. The findings indicate that AI-enabled applications can significantly improve the efficiency of the analytical process and reveal the linguistic patterns that are not available to ordinary analysis. Yet, another problem like bias, explainability and ethics issues is significant. The research provides a conclusion that although AI has become an inseparable part of linguistics today, there is a need to establish a balanced approach of using computational methods and knowledge of human linguists to be sustainable and ethical.

  • References

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