Assessing neural machine translation of court documents: A case study on the translation of a Spanish remand order into English

Abstract

The court translation sector is showing considerable growth in demand due to the increasing number of proceedings involving people who do not speak the language used by the authorities, and particularly across the European Union (EU) since the passing of recent legislation that has enshrined the right to translation of essential documents in criminal proceedings (Brannan, 2017). For the translation of legal texts, machine translation (MT) is not viewed with optimism due to its disregard for the purpose and recipient of the translation (e.g., Wiesmann, 2019; Roiss, 2021), despite its potential for saving time and the benefits it offers at the terminological and phraseological levels (Killman, 2014) or at the level of syntax (e.g., Heiss & Soffritti, 2018; Mileto, 2019; Wrede et al., 2020). The aim of this article is to discuss whether translators can benefit from MT when engaging in the challenging yet highly in-demand activity of court translation. This article assesses the quality of English translations of a Spanish remand order produced by three different neural machine translation (NMT) systems (DeepL, eTranslation, and Google Translate), using TAUS evaluation guidelines.