The Dual Impact of Speech Recognition Technology on Simultaneous Translation

Currently, technologies such as artificial intelligence, big data, speech recognition technology, and machine translation are having an increasing impact on the field of human translation. On the one hand, they challenge manual translation, but on the other, they help and improve it. This article analyzes the positive and negative effects of speech recognition technology in simultaneous translation on the interpretation process, examines and analyzes the results of previous studies, and provides some recommendations to other translators on the use of speech recognition technology in simultaneous translation. The author emphasizes that speech recognition technology has a significant impact on the simultaneous translation process, improving its quality and efficiency. The dual impact of this technology on translation synchronization is, on the one hand, in automating routine operations, reducing the burden on the translator, and on the other, in making work more difficult, increasing the requirements for reaction speed and accuracy. Automation of text input processes using voice technology makes it possible to transfer source speech into the target language faster, minimizing delays between speakers and listeners. However, in order to work successfully, translators have to adapt to new conditions, promptly correcting machine recognition results in order to avoid mistakes. The study examines the possibilities and limitations of modern speech recognition systems in relation to simultaneous translation, identifying key success factors for integrating technology into this process. Special attention is paid to the interaction of the human factor and algorithms, which determines the future development of synchronous interpretation. The work highlights the need to train specialists who are able to effectively use modern tools while maintaining high-quality communication. © 2025 Elsevier B.V., All rights reserved.