What do translators think about GPT?

>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. [LINK] [VIDEO]

I tried it on a video I made a few months ago. Here’s the original, in which I speak English: [VIDEO] And here are the first two and a half minutes with me dubbed into Japanese: [LINK] Aside from some pacing problems, the voice and intonation sound quite good to me. But anyone listening to the translation alone would find it hard to follow, as the tool seems to have mistranscribed some of my English and mistranslated some of the rest. (I understand Japanese.) The dubbing would probably be a lot better if I had spoken English more slowly and with awareness that what I said would be interpreted into another language.

I think it did pretty well. No offense as your original video is still really great for a native English speaker (me) to listen to, but the English speech varies in pace a lot, sometimes you speak incredibly quickly, at such a pace that you even miss some syllables or blend them together for example [VIDEO] it sounds like you said "technogial" or "technodule" rather than "tech-no-log-ical". So I can understand that a machine may make mistakes on this; don't worry, as a Kiwi I mumble and do this too ha ha. But the Japanese result is still already very very impressive even if I haven't spoken since I was 15 and over there on exchange (and stopped learning once I realise they romanise everything, why label a bottle with appuru jyusu when you have RINGO SHIRU!)

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