TRAINING THE AUGMENTED INTERPRETER TODAY

Author:

ANTONOVA A.M.1

Affiliation:

1. Herzen State Pedagogical University

Abstract

Any interpretation training programme aspiring to excellence must be closely connected with the professional world and make effective use of innovative teaching methods, cooperation with external stakeholders, and modern technologies in order to ensure a high quality of learning. This paper focuses on the different aspects of ‘quality’ in light of the advent of new technologies and the changing nature of the interpreting profession. Interpretation training programmes must learn today how to prepare a widely employable interpreter to survive the pressures of the professional world. A scenario-based approach, that simulates work-like situations, is effective in interpretation training. The paper will focus on mock conferences, as its most effective teaching practice. Mock conferences help to enhance the authenticity and diversity of lifelike situations in class, provide the students with contextualised practice that helps to develop non-linguistic competences. The latest technologies, e.g. ICTs, AI, etc., offer a new degree of automation to all professional language mediation activities, calling for a rethinking of the interpreter’s skillset. The future will accommodate both artificial and human interpreting, and the bar for humans will be raised. The interpretation students must learn how to use the latest technologies for the benefit of the client. A new, augmented interpreter profile includes the combination of the classical competences (interpretation, language and cultural, interpersonal, ethical, etc.) and technological competences which must be used for the benefit of the client and the events at which the interpreter works. The paper also explores the value added by human interpretation to communication, such as depth of message comprehension, teamwork, shared responsibility and liability and, most importantly, the value of the ‘interpreter who cares’.

Publisher

Moscow University Press

Reference30 articles.

1. Alekseeva I.S., Antonova A.M. 2021. Struktura dinamicheskoi obrazovatel'noi sredy matrichnogo tipa (na primere Sankt-Peterburgskoi vysshei shkoly perevoda pri RGPU im. A. I. Gertsena) [An Innovative Dynamic Matrix-Type Learning Environment Based on the Example of the St. Petersburg School of Conference Interpreting and Translation, Herzen University, Russia]. Vestnik NSU. Series: Linguistics and Intercultural Communication, vol. 19, no. 4, pp. 103-116. (In Russ.).

2. Angelelli C.V. 2004. Revisiting the Interpreter's Role. Amsterdam: John Benjamins.

3. Ardito G. 1999. The Systematic Use of Impromptu Speech in Training Interpreting Students. The Interpreters' Newsletter, no. 9, pp. 177-189.

4. Bühler H. 1986. Linguistic (semantic) and extralinguistic (pragmatic) criteria for the evaluation of conference interpretation and interpreters. Multilingua, no.5(4), pp. 231–235.

5. Chui M., Manyika J., Miremadi M. 2016. Where machines could replace humans — and where they can’t (yet). McKinsey Quarterly, no. 3, pp. 58–69. URL: https://www.mckinsey.com/business-functions/operations/our-insights/mckinsey-quarterly-2016-number-3-overview-and-full-issue (accessed: 03.12.2021).

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