AI Translation Tools Compared for Real Publishing Work
I translated the same article through four AI translation tools and rated the output for publishability. The results were not what I expected. I translate content for audiences in English, Spanish, and Japanese. I do not speak the last two fluently enough to publish without help, so I rely on AI translation tools. To pick the right one, I ran the same 800-word article through four tools and had a native speaker rate each output. Here is, with the caveat that translation quality is language-pair dependent. What I found for English-to-Spanish and English-to-Japanese may not hold for other pairs. The Test Setup The source article was a practical guide with technical terms, a few idioms, and a casual but precise tone. I used the same prompt for each tool: translate the following into the target language, preserve the tone, keep technical terms in English where the target audience would expect them, and flag any phrase that needs cultural adaptation. I did not pre-process the source. I wanted to see default behavior. A native speaker for each target language rated the output on a scale of one to five across three dimensions: accuracy, fluency, and tone match. Anything below a four on accuracy meant the translation was not safe to publish without correction. I also asked the reviewers to flag specific problem areas so I could see patterns across tools.