Technological Advancements in Translation and Interpreting: A Decade of Progress - Research Paper

Introduction

The past several decades have seen a significant rise and advance technological innovation. According to Varela-Salinas (2019), this development has seen the creation and deployment of unprecedented growth in regards to translation and interpreting technology as a conduit for inter-lingual communication. These interpretation technologies have resulted in increased quality and productivity in the concept of translation; and significantly advanced international communication (Duoxiu & Teng 2010; Doherty, 2016). The craze of artificial intelligence, big data, and cloud computing has swept the world. The advancement of science and technology will inevitably promote industrial innovation (Saz, Lin, & Eskenazi, 2015). The interpretation industry will necessarily undergo profound changes due to the emergence of interpretation technology. Baker and Saldanha (2019) noted that the relationship between interpreting technology and interpreters is critical to the future development of the industry. Interpreting technology has changed the translator's traditional translation mode, affecting the translator's energy distribution, and put forward new requirements for the translator's ability, especially the technical ability, accompanied by the diversification of the translator's role (Venuti, 2017). Such changes are closely related to the translator's development, future translator training, and industry trends.

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Research Questions

• What is the impact of interpreting technology on translator's; own cognition and mastery of interpreting techniques (questionnaires);
• What is the effect of interpreting techniques on translation quality (contrast experiments)
• How has this interpreting technology changed the translator's energy allocation during interpreting, and how do they adjust to these new scenarios, roles, and ability requirements?

Research Objectives

With a sustained growth and development in the translation technology sector, the translation memory system and the machine translation framework have, over time, become common tools among expert translators. Consequently, this research article will:

• Provide a clear introduction of the concept of the translation memory system and the machine translation framework;
• explain some key terminologies, providing an overview of key concepts while at the same time cataloging the progressive development of these technologies to deliver effectively and recommendations on the possible direction for future study.
• How has the continued development and growth of translator and interpretation technologies affected china's entrance as a player in the world stage?

Statement of the Problem

Innovation in technology has significantly changed the overall approach and translation practices. The interaction between technology and translators has resulted in more excellent energy distribution, and it is increasingly becoming a requirement for all translators. This raises the question of how technological innovation will affect translator ability and future translator training and industry trends to align with the input of translating and interpreting technology from China.

Literature Review

Doherty (2016) takes this position that these interpretation technologies have resulted in increased quality and productivity in the concept of translation; and significantly advanced international communication. The innovation in the translating technology has changed the translator's traditional translation mode, consequently affecting the energy distribution of the translator, thus putting forward new requirements for the translator's ability, especially the technical ability, accompanied by the diversification of the translator's role (Cadwell, O'Brien, & Teixeira, 2018). It is imperative to recognize that these impacts are linked to individual development, potential future training programs, and the sector's future trends.

The research will present hat the need for translator innovation and technology as a result of china's position on the world stage has spurred increased interest in the sector. Thus, new market players have emerged. This concept is advanced by Fantinouli (2018), who argued that the growth in the industry had created direct competition for service providers within china with the emergence of computer-assisted interpretation and translation technologies. The language translation sector is an imperative foundational premise to china's capacity and ability to become an active participant at the world stage (Baker & Saldanha, 2019; Jakobsen & Mesa-Lao, 2017). The research projects that the continued development and growth of translator and interpretation technologies augment and significantly improve china's position as a significant player on the world stage. Gaspari, Almaghout, and Doherty (2015) held that the emergence of interest in this sector has resulted in an influx of new industry players to compete with the few established websites, both local and international, seeking to meet the needs of the user. This underlines the growing and important role these technological innovations play, as the need for translator services increase (Doherty, 2016).

The research will also present the progressive development of interpretation and translation technologies such as the Computer-assisted interpretation and translation technologies. Fantinouli (2018) defined computer-assisted interpreting as a form of oral translation where human interpreters utilize specially designed software to facilitate and support the critical aspects of translating with the primary objective of augmenting, and to a slight extent, productivity. Xu, Guo, and Guo (2007) characterized these technologies as specially designed to aid interpreters in developing glossaries with the capacity and capability to integrate an extensive range of terms and resources. These technologies utilize advanced natural language process characteristics, for example, identification of crucial topic terminologies, automatic speech recognition, and translation, summarization, automatic terminology extraction, among others (Cadwell et al., 2018).

Significance of the Study

The ever-expanding trend of globalization, sustained by technological innovation such as translation and interpretation technology, has highlighted the need and importance of developing a modern innovative and effective solution to the ever-existent problem of the language barrier (He, 2016). This study will play a key role in investigating the development of interpretation technology and its impact on translator development. The study will be imperative in informing the understanding of how these translation technologies are influencing the translator's development, future translator training, and industry trends.

Research Methodology

Qualitative research design.

The qualitative research design refers to a research method used by researchers and scientists to study human habits and behaviors and investigate trends. The qualitative research design will be used in this study because it is an interactive approach whereby the researchers interact with people either directly or indirectly (Lewis, 2015). Data will be collected through interviews, individual case studies, observation, and survey techniques. Qualitative research design is easy to plan and flexible method of research, which is suitable in both small and large scale sampling (Lewis, 2015). Qualitative research design is grouped into five approaches, which include: case study, grounded theory, narrative, phenomenological, and ethnography approaches (Tetnowski, 2015). To ensure rigor in the research, the "triangulation" method will be used to conduct analysis and research from different dimensions, including theoretical analysis, qualitative analysis, and questionnaires to enhance the credibility of the study (Renz, Carrington, & Badger, 2018). This technique is essential in qualitative research methodology, characterized by the use of a wide-ranging pool of sources on the issue under research. The triangulation method was chosen for its ability to be used as a strategy that can be used to conduct a validity test by the data or information convergence from diverse sources (Renz et al., 2018). The data collected will be analyzed through coding to establish critical themes and implications of using technology on interpreters and translators.

References

Baker, M., & Saldanha, G. (2019). Routledge encyclopedia of translation studies. Routledge. Retrieved from http://docshare02.docshare.tips/files/28809/288093806.pdf

Cadwell, P., O'Brien, S., & Teixeira, C. S. (2018). Resistance and accommodation: factors for the (non-) adoption of machine translation among professional translators. Perspectives, 26(3), 301-321. Retrieved from https://www.tandfonline.com/doi/abs/10.1080/0907676X.2017.1337210

Doherty, S. (2016). "The Impact of Translation Technologies on the Process and Product of Translation." International Journal of Communication, 10, 23. Retrieved from http://ijoc.org/index.php/ijoc/article/view/3499

Duoxiu, Q. & Teng X. (2010) "Localization and Translation Technology in the Chinese Context. Department of Translation and Interpretation Beihang University, Beijing, China. Retrieved from http://www.translationindustry.ir/Uploads/Pdf/Localization%20and%20Translation%20Technology%20in%20the%20Chinese%20Context.pdf

Farwell, D. (2006). Computational Linguistics and Machine Translation Research and Development. Tradumatica: traduccio i technologies de la informacio i lacomunicacio, (4). Retrieved from https://www.raco.cat/index.php/Tradumatica/article/view/56006

Gaspari, F., Almaghout, H., & Doherty, S. (2015). A survey of machine translation competences: Insights for translation technology educators and practitioners. Perspectives, 23(3), 333-358. Retrieved from https://www.tandfonline.com/doi/abs/10.1080/0907676X.2014.979842

He, D., Xia, Y., Qin, T., Wang, L., Yu, N., Liu, T. Y., & Ma, W. Y. (2016). Dual learning for machine translation. In Advances in Neural Information Processing Systems (pp. 820-828). Retrieved from https://papers.nips.cc/paper/6469-dual-learning-for-machine-translation.pdf

Jakobsen, A. L., & Mesa-Lao, B. (Eds.). (2017). Translation in Transition: Between cognition, computing, and technology (Vol. 133). John Benjamins Publishing Company. Retrieved from https://research.cbs.dk/en/publications/translation-in-transition-between-cognition-computing-and-technol

Lewis, S. (2015). Qualitative inquiry and research design: Choosing among five approaches. Health promotion practice, 16(4), 473-475. Retrieved from https://journals.sagepub.com/doi/abs/10.1177/1524839915580941

Renz, S. M., Carrington, J. M., & Badger, T. A. (2018). Two strategies for qualitative content analysis: An intramethod approach to triangulation. Qualitative health research, 28(5), 824-831. Retrieved from https://journals.sagepub.com/doi/abs/10.1177/1049732317753586

Saz, O., Lin, Y., & Eskenazi, M. (2015). Measuring the impact of translation on the accuracy and fluency of vocabulary acquisition of English. Computer Speech & Language, 31(1), 49-64. Retrieved from https://www.sciencedirect.com/science/article/pii/S0885230814001223

Tetnowski, J. (2015). Qualitative case study research design. Perspectives on Fluency and Fluency Disorders, 25(1), 39-45. Retrieved from https://pubs.asha.org/doi/abs/10.1044/ffd25.1.39

Varela-Salinas, M. J. (2019)....