Work

Machine learning: Implications for translator education

Year: 2017

Type: article

Abstract: Machines are learning fast, and human translators must keep pace by learning with, from and about them. Deep learning (DL) and neural machine translation (NMT) are set to change the reality of translation and the distributions of tasks. Although theoretical and practical courses on computer-aided and/or machine translation abound, less attention has been paid to DL and NMT in most translation programmes. The challenge for translation education is to give students the knowledge and toolkits to learn when and how to embrace the new technologies, and to exploit how and when the added value of human intuition, creativity and ethics can and should be deployed.

Source: Lebende Sprachen

DOI: 10.1515/les-2017-0021

Authors: Gary Massey, Maureen Ehrensberger-Dow

Institution: ZHAW Zurich University of Applied Sciences

Language: English

Topic: Translation Studies and Practices

Subfield: Language and Linguistics

Field: Arts and Humanities

Domain: Social Sciences

SDG: Quality education

Open Access status: green

Funder: Zürcher Hochschule für Angewandte Wissenschaften