A student asked me recently about GenAI’s performance with slightly unusual language combinations, like Swedish to French.
This reminded me that one of our CotranslatorAI power users successfully translates between Dutch and Romanian. His experience shows that the quality is impressive, even in less common language pairs.
Here are some things to keep in mind, though.
1. It’s all about the data, not the difficulty.
Generative AI doesn’t find any language inherently hard or easy; it’s the amount and quality of data available that matter. Also, the AI doesn’t need an abundance of data specifically between languages in your pair.
I can’t say anyone completely understands what’s happening here, but with the data it has for each language, the AI somehow forms the internal connections, enabling effective translation.
2. Language data quantity isn’t everything.
Although more data means better AI performance, the difference in quality isn’t linear.
For instance, I would estimate that languages like Spanish and French probably perform at 95% or higher than what you might expect from English, even though the amount of data is much less.
3. Rely on your methodology.
Make sure you’re using the right techniques to get the best results from using GenAI in your specific language pair. A best-practices approach can compensate for less data, enhancing your output and translation quality dramatically.
Keep experimenting with your language pair and methodology to uncover just how powerful GenAI can be in supporting your translation work.