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Based on what I read in the article, MT was used as an experiment and proof of concept, and dedicated translation was done for the full release. Was that not th

Based on what I read in the article, MT was used as an experiment and proof of concept, and dedicated translation was done for the full release. Was that not the case? Was the workflow MT -> human translation? If so thats honestly such a lazy followthru given the technical hurdles overcome wrt the font tech

ndiddy 7mo ago
From the Github repo (https://github.com/ExxistanceDC/Segagaga-English-Translation https://github.com/ExxistanceDC/Segagaga-English-Translation), the translation went through a process called MTPE (Machine translation, post-editing). This works just like it sounds. The initial translation is done with machine translation, then human translators review and edit the resulting translation to try to correct any mistakes. > What I call the “playtesting translation” — a base translation that allowed the artists and playtesters to get started early and understand what they were working on — was developed using a combination of DeepL and ChatGPT 4o/4.5. That translation then went through a substantial, months-long human translator review. I don't think that the end product feels “machine-translated,” but that’s ultimately for you, the player, to judge.
- jsheard 7mo ago
  > MTPE (Machine translation, post-editing). This works just like it sounds. The initial translation is done with machine translation, then human translators review and edit the resulting translation to try to correct any mistakes. And the consensus among professional translators is that MTPE only saves time if you're willing to accept a half-assed result. For them to edit MT up to the standard of manual translation takes just as much expertise and effort as translating it manually in the first place.
  - vova_hn2 7mo ago
    > consensus among professional translators [citation needed]
    - jsheard 7mo ago
      https://blog.gts-translation.com/2025/04/07/the-state-of-machine-translation-post-editing-mtpe-in-2025-what-translators-think/ https://blog.gts-translation.com/2025/04/07/the-state-of-mac... > 12.08% [of translators] say MTPE produces high-quality output. > A significant portion (around 50%) of respondents do not offer discounts for MTPE work, arguing that post-editing can take as much time as traditional translation. > Among those who do offer discounts, the most common range is between 10-30%.
  - laksjhdlka 7mo ago
    > And the consensus among professional translators is that MTPE only saves time if you're willing to accept a half-assed result. I have no particular interest in translation, but clearly when the person saying X is bad depends financially on you not buying X, you must take their word with a grain of salt.
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  - pimlottc 7mo ago
    It’s also used to shortchange professional translators by paying them a lower rate for MTPE jobs
- RobRivera 7mo ago
  Oh boo hoo. Just boooooo. Disappointed. Gif As a side bar, I found it funny how in a Stanford lecture teaching various routes to training llms on the Machine Translation benchmark, the sample used was a French to English translation of 'the teddy bear is blue' or something similar. After the lecture I reviewed the current production grade google translate...it butchered the translation I wouldnt trust machine translation.
- tomalbrc 7mo ago
  And according to contributors like 645 it’s a bad machine translation.
- nekooooo 7mo ago
  the end product is incredibly stilted, missing in-jokes, has misnamed items and ruins like half the puns and wordplay in the game. it also switches past/present/future cases and is really inconsistent with indefinite articles.

ndiddy 7mo ago

From the Github repo (https://github.com/ExxistanceDC/Segagaga-English-Translation https://github.com/ExxistanceDC/Segagaga-English-Translation), the translation went through a process called MTPE (Machine translation, post-editing). This works just like it sounds. The initial translation is done with machine translation, then human translators review and edit the resulting translation to try to correct any mistakes. > What I call the “playtesting translation” — a base translation that allowed the artists and playtesters to get started early and understand what they were working on — was developed using a combination of DeepL and ChatGPT 4o/4.5. That translation then went through a substantial, months-long human translator review. I don't think that the end product feels “machine-translated,” but that’s ultimately for you, the player, to judge.

jsheard 7mo ago
> MTPE (Machine translation, post-editing). This works just like it sounds. The initial translation is done with machine translation, then human translators review and edit the resulting translation to try to correct any mistakes. And the consensus among professional translators is that MTPE only saves time if you're willing to accept a half-assed result. For them to edit MT up to the standard of manual translation takes just as much expertise and effort as translating it manually in the first place.
- vova_hn2 7mo ago
  > consensus among professional translators [citation needed]
  - jsheard 7mo ago
    https://blog.gts-translation.com/2025/04/07/the-state-of-machine-translation-post-editing-mtpe-in-2025-what-translators-think/ https://blog.gts-translation.com/2025/04/07/the-state-of-mac... > 12.08% [of translators] say MTPE produces high-quality output. > A significant portion (around 50%) of respondents do not offer discounts for MTPE work, arguing that post-editing can take as much time as traditional translation. > Among those who do offer discounts, the most common range is between 10-30%.
- laksjhdlka 7mo ago
  > And the consensus among professional translators is that MTPE only saves time if you're willing to accept a half-assed result. I have no particular interest in translation, but clearly when the person saying X is bad depends financially on you not buying X, you must take their word with a grain of salt.
  - deleted 7mo ago
    [deleted]
  - deleted 7mo ago
    [deleted]
- pimlottc 7mo ago
  It’s also used to shortchange professional translators by paying them a lower rate for MTPE jobs
RobRivera 7mo ago
Oh boo hoo. Just boooooo. Disappointed. Gif As a side bar, I found it funny how in a Stanford lecture teaching various routes to training llms on the Machine Translation benchmark, the sample used was a French to English translation of 'the teddy bear is blue' or something similar. After the lecture I reviewed the current production grade google translate...it butchered the translation I wouldnt trust machine translation.
tomalbrc 7mo ago
And according to contributors like 645 it’s a bad machine translation.
nekooooo 7mo ago
the end product is incredibly stilted, missing in-jokes, has misnamed items and ruins like half the puns and wordplay in the game. it also switches past/present/future cases and is really inconsistent with indefinite articles.