Speech Translation: A Bibliometric Analysis of Research Trends and Contributions based on Scopus Data
Speech Translation: A Bibliometric Analysis of Research Trends and Contributions based on Scopus Data |
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| © 2025 by IJETT Journal | ||
| Volume-73 Issue-4 |
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| Year of Publication : 2025 | ||
| Author : Maria Labied, Abdessamad Belangour, Mouad Banane |
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| DOI : 10.14445/22315381/IJETT-V73I4P116 | ||
How to Cite?
Maria Labied, Abdessamad Belangour, Mouad Banane, "Speech Translation: A Bibliometric Analysis of Research Trends and Contributions based on Scopus Data," International Journal of Engineering Trends and Technology, vol. 73, no. 4, pp.159-179, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I4P116
Abstract
This study provides a comprehensive bibliometric analysis of speech translation research from 2000 to 2024, leveraging Scopus database data to identify key trends, influential contributions, and collaborative networks in this rapidly evolving field. We map the transition from traditional statistical methods to advanced neural and deep learning approaches in speech translation technologies by analysing publication patterns, citation metrics, and research themes. Our findings highlight the most prolific authors, institutions, and countries, along with the leading journals and conferences that serve as primary outlets for high-impact research. Notably, the analysis reveals a substantial increase in research activity and a growing focus on end-to-end translation systems and multilingual corpora, demonstrating the field's shift towards scalable and effective real-world applications. The importance of international collaborations and interdisciplinary research is emphasized, showcasing their role in driving innovation and addressing complex challenges. This bibliometric analysis provides valuable insights for researchers, practitioners, and policymakers, offering a foundational understanding of the current landscape and future directions of speech translation research. By elucidating the dynamics of this field, our work aims to inspire further advancements and enhance the impact of future research efforts.
Keywords
Speech Translation, Bibliometric Analysis, End-to-End speech translation, Direct speech translation, Machine translation, Automatic speech translation.
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