Sustaining Disruption? On the Transition from Statistical to Neural Machine Translation

Main Article Content

Dorothy Kenny

If statistical machine translation (SMT) was a disruptive technology, then neural machine translation (NMT) is probably a sustaining technology, continuing on a trajectory already established by SMT, and initially evaluated in much the same way as its predecessor. Seeing NMT in this light may be a useful corrective to the hype that has surrounded its introduction.

Keywords
Disruptive innovation, machine translation, statistical MT, neural MT, quality metrics, mobility

Article Details

How to Cite
Kenny, Dorothy. “Sustaining Disruption? On the Transition from Statistical to Neural Machine Translation”. Tradumàtica: traducció i tecnologies de la informació i la comunicació, 2018, no. 16, pp. 59-70, https://raco.cat/index.php/Tradumatica/article/view/350193.
Author Biography

Dorothy Kenny, Dublin City University

Dorothy Kenny is Professor in the School of Applied Language and Intercultural Studies (SALIS) at Dublin City University, where she lectures in translation theory, translation technology, terminology and corpus linguistics.