Since 2023, translators for the Parliament of Canada have had the option to use neural machine translation (NMT) technology provided by the National Research Council of Canada (NRC) to support their work in translating parliamentary publications between French and English. We present our analysis of an anonymized dataset of translators’ interactions with our Hawkeye MT systems, collected since their introduction and covering a period of 2.5 years. This data provides a unique perspective on how translators interact with the systems, how their use evolved over time and how it impacts the nature of their translations.

Translators at the Canadian Parliament currently have access to a neural machine translation system as an optional tool integrated into their translation environment, whose output they can use for postediting (rather than translating from scratch); this provides a valuable opportunity to study the dynamics of MT adoption in professional settings. We report on a user study that investigates how and why translators choose to interact with this tool. Using a mixed-methods approach, we examined both human and technical factors that influence the adoption or non-adoption of the system. Drawing on our findings, we advocate for a user-centred approach to MT integration within professional translation workflows.

The Parliament of Canada’s translation workflow includes access to a specialized neural machine translation (NMT) system. This study analyzes post-editing (PE) activity to identify the types of edits translators make when interacting with the NMT system, as well as the frequency, nature, and severity of errors encountered. We compare translations produced with and without the use of this NMT system to evaluate potential differences in edit patterns. To complement this analysis, we draw on insights from a user study. Our findings explore how translators’ perceptions align with observed PE patterns and how their feedback can inform strategies to better understand, and possibly mitigate, some of the errors observed.