laserembeddings VS firefox-translations

You're pretty much right on the money. For ParaCrawl[1] (which I worked on) we used fast machine translation systems that were "good enough" to translate one side of each pair to the language of the other, see whether they'd match sufficiently, and then deal with all the false positives through various filtering methods. Other datasets I know of use multilingual sentence embeddings, like LASER[2], to compute the distance between two sentences.

Both of these methods have a bootstrapping problem, but at this point in the MT for many languages we have enough data to get started. Previous iterations of ParaCrawl used things like document structure and overlap of named entities among sentences to identify matching pairs. But this is much less robust. I don't know how they solve this problem today for low-resource languages.

[1] https://paracrawl.eu

[2] https://github.com/yannvgn/laserembeddings

I've been using LASER from Facebook Research via https://github.com/yannvgn/laserembeddings to accept multi-lingual input in front of the the domain-specific models for recommendations and stuff (that are trained on English annotated examples).

Interestingly, I think this is actually related to the offline translation features built into Firefox. Both are products of "Project Bergamot", but the Mozilla-maintained version was later merged into the Firefox application:

https://browser.mt/

https://blog.mozilla.org/en/mozilla/local-translation-add-on...

https://hacks.mozilla.org/2022/06/training-efficient-neural-...

https://github.com/mozilla/firefox-translations

https://firefox-source-docs.mozilla.org/toolkit/components/t...

Extra webpage with screenshot and links, impossible to search for normally:

https://translatelocally.com/downloads/

Does one thing and does it well.

Oh— For downloading models, it's much easier to pipe/`xargs` `translateLocally --available-models` into `translateLocally -d` than go through the GUI.

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Other self-hostable translation tools:

https://www.apertium.org/index.eng.html

- Traditional rule-based translation. Seems to work pretty well, but no good desktop frontend.

https://www.argosopentech.com/

- Works, but crashy desktop app.

https://libretranslate.com/

- API wrapping Argos Translate.

https://lingva.thedaviddelta.com/

- Google Translate scraper/privacy frontend.

https://euroglot.com/

- Proprietary, subscription trialware.

You can submit feature requests to this Github repository: Add Japanese Translation.

I reported this to https://github.com/mozilla/firefox-translations/issues/688

Mozilla did release DeepSpeech[0] and Firefox Translation[1] (the latter of which they included in Firefox, to offer client-side webpage translations.)

They definitely have fewer resources than OpenAI, and they do not produce SOTA research (their publications have plummeted to 1/year anyway[2]). So the only way for them to make progress is to seek government grants or make challenges like these.

This challenge is unlikely to be profitable for the winning team: the expected value of winnings are likely around $1K when taking into account the probability that another team gets a better rank, but ML research projects are often more expensive (recently, Alpaca spent upwards of $600 on computation alone; and of course pretraining large models is much more expensive). So the main gain will be publicity.

[0]: https://github.com/mozilla/deepspeech

[1]: https://github.com/mozilla/firefox-translations/

[2]: https://research.mozilla.org/

Firefox has an offline translation extension: https://github.com/mozilla/firefox-translations

That will be released in the next version: https://github.com/mozilla/firefox-translations/commit/af29a6ca83c4e98566d510c0f150667a43e506d2

https://github.com/mozilla/firefox-translations/issues/374

Maybe it will get implemented

Did you install Firefox Translations? If so, the feature to turn off translation bar will come very soon in the next version according to this bug.

See https://github.com/mozilla/firefox-translations for in development languages.