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Website | tatoeba.org |
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Website | apertium.org |
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Based on our record, Tatoeba seems to be a lot more popular than Apertium. While we know about 32 links to Tatoeba, we've tracked only 3 mentions of Apertium. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
OP may I suggest you contribute these to https://tatoeba.org/en/ ? Source: 10 months ago
The reason some of the sentences are a bit weird is that they are from tatoeba it's a great source of sentences translated into different languages :). Source: 12 months ago
Tatoeba: Search for words (either in English or Chinese), and find sentences with those words. Add those words + sentences to your deck. Source: about 1 year ago
And you have to complete the cloze with "jours". The sentences are compiled automatically from Tatoeba[1], the cloze deletion is done on the least-common word[2]. This combines vocabulary with grammar. I didn't like the Clozemaster UI so I wrote a script to make the clozes myself: https://borretti.me/article/building-diy-clozemaster But automatic approaches are not great. Later I asked GPT-4 to make these... - Source: Hacker News / about 1 year ago
Https://tatoeba.org/en - but not so much on the grammatical analysis. I don't know anything that does that. Source: about 1 year ago
This is very cool, looking forward to it! I've been doing the same thing with Spanish Wikipedia articles for a while, using a few lines of Bash + Regex. I was using Apertium for it. https://apertium.org/ It's definitely worse than most ML-based solutions, but it works reliably and fast; you can run it entirely offline. With Spanish translations, the main problem I was facing is lack of vocabulary, so I created - Source: Hacker News / 8 months ago
I used to keep track of the state of machine translation some years back. I think the way you measure the success of an automated translation is edit distance, i.e. How many manual edits you need to make to a translated text before you reach some acceptable state. I suppose it's somewhat subjective, but it is possible to construct a benchmark and allow for multiple correct results. The best resources I knew back... - Source: Hacker News / almost 2 years ago
Apertium is one of them. We make open-source rule-based machine translation systems, and our core tools are in C++. A few of our proposed ideas involve modifying those C++ tools with new features or improvements to existing features. Source: about 3 years ago
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