Despite dealing with a lot (Daily log, maiki - #7 by maiki, Health log, maiki - #11 by maiki), I’ve been setting up a new process using machine-learning auto-translation tools to assist translators with the work of translating hypermedia documents (text, images, audio, video, forms, maps, etc…) for the public.
We had an okay system before, but the pandemic and other factors have introduced difficulties, such as training new translators on the system, even if they are translating a single piece of content. This new process will accommodate both our in-house translators working directly on the platform, as well as sending previews for vetting and a public-facing reporting system so anyone give us feedback.
The platform has many users adding content, and each dept. or campaign might have it’s own resources to contribute to translation (translators on the team, special budget, that sorta thing). This new system allows us to be more flexible and accept translation efforts in a variety of channels.
Which is good, the more we can push translation “behind the curtain” the less of a pain-point it (and it definitely is). But with this hybrid approach, we get the cost- and effort-savings from auto-translation, while ensuring the specialized topic (city planning and transportation information and feedback) is understandable by a human.