
Can GPT-4 translate literature?
About this video
Tom Gally, a former professional translator and University of Tokyo professor, discusses in March 2023 whether GPT-4 and similar models could translate literary and popular fiction. He gives his assessment of Japanese-to-English quality.
Why it appears in the archive
Cited as an expert's first-hand evidence that GPT translation is near human quality for distant language pairs.
AI-generated summary and labels from the source dataset; verify important details against the video. Source & credits.
From the Hacker News discussion
Are you giving it multiple paragraphs to translate at once so that it has enough context for a good translation? If so, would you mind sharing a sample input and output that you found unsatisfactory? In "Can GPT-4 translate literature?" (Mar 18, 2023) [ [VIDEO] ], Tom Gally, a former professional translator and current professor at the University of Tokyo, said: > …the point is, to my eye at least, the the basic quality of the translation [from Japanese to English] is as good as a human might do, and with some relatively mild editing by a sensitive human editor, it could be turned into a novel that would be readable and enjoyable.
Read original comment ↗>about machine translation and looked at some results of translating between English and French. It was difficult to find any fault with the translation. This has never been the case for distant language pairs till GPT. That is a pretty big change. [VIDEO]
Read original comment ↗>but nobody in the very well funded translation industry has a GPT powered translation engine for the key reason that it's not ready for production. Translator for 20 years talking about using GPT for Japanese-English. [VIDEO] [LINK]
Read original comment ↗As I explained in a sister comment, it is not possible to rate translation quality objectively, as opinions and positions about what constitutes a good translation vary. But in my tests of reasoning models since the release of o1-preview, they have not seemed as reliable as the straight nonreasoning versions of ChatGPT, Claude, or Gemini. The translation process itself usually doesn’t seem to require the kind of multistep thinking those reasoning models can be good at. For more than a year, regular LLMs, when properly prompted, have been able to produce translations that would be indistinguishable from those of some professional translators for some types of translation. General-purpose LLMs are best for translating straight expository prose without much technical or organization-specific vocabulary. Results are mixed for texts containing slang, dialogue, poetry, archaic language, etc.—partly because people’s tastes differ for how such texts should be translated. Because most translators are freelancers, it’s hard to get a handle on what impact LLMs have been having on their workloads overall. I have heard reports from experienced translators who have seen work drop off precipitously and have had to change careers, while others report an increase in their workloads over the past two years. Many translation jobs involve confidential material, and some translators may be hanging onto their jobs because their clients or employers do not allow the use of cloud-based LLMs. That sa
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