I really hope you check with native Cree speakers before you publish a system like this. Smaller language communities are already being hurt by low-quality gene

I really hope you check with native Cree speakers before you publish a system like this. Smaller language communities are already being hurt by low-quality generated text. See also https://news.ycombinator.com/item?id=35300603 https://news.ycombinator.com/item?id=35300603 for an experience of GPT with the language Northern Saami. Also, back-translation was never a good evaluation method. Say I don't know English; and I make a new system that calls Google Translate word for word. I back-translate the Norwegian input "den sykkelen kunne jeg gjerne hatt" and my word-for-word system gives "it the bike could I happily hat". Now I evaluate that whole sentence by putting it into Google Translate and presto I get "den sykkelen kunne jeg gjerne hatt" – can I conclude that word-for-word Google Translate is perfect? Or even worse, if you use the same system in both directions, anything that's looks like a bijection if you squint will do (reverse then reverse, transliteration into Canadian syllabics then back, encrypt/decrypt, map each word to a number, etc.). If you have a bilingual corpus of Cree text, then you can get some automated measures (some popular ones listed at https://wiki.apertium.org/wiki/Evaluation https://wiki.apertium.org/wiki/Evaluation ), but it would have to be a corpus you didn't find online since otherwise GPT-4 has it in its training data and it the numbers will not be valid for sentences that are not in that corpus.