It's based on pedagogy principles like spaced repetition and the testing effect. I genuinely think it's probably the most efficient language learning app out there, though it's less polished since I only work on it in my spare time. (And because I haven't tried every language learning app out there, I can't really conclusively make that determination, but I still think it's the best for reasons I'll get into.)
By the way, the frontend is mostly Rust compiled to WASM, which enabled performance optimizations that would've been tough in JavaScript. One other thing: the app is local-first and has cross-device sync based on CRDTs, which I figure should be a hit here. Honestly, that was pretty much as much work as the entire rest of the app combined. The source code is here: https://github.com/anchpop/yap
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Building this taught me a lot about spaced repetition. The core idea with Yap is that it tests you with sentences that contain words you need to practice. But this gets tricky because words have multiple uses. If you mistranslate a word used one way, practicing it in a different context isn't helpful.
My solution uses NLP (using spaCy) to annotate words with their parts of speech and lemmas, which distinguishes different uses and conjugations of the same word. I also maintain a database of "multi-word terms", because many phrases (such as "a lot") need to be learned as units.
For spaced repetition, the scheduler is FSRS, which is state of the art.
For users with prior language exposure, I automatically adjust difficulty by analyzing word frequency against what they seem to find easy, helping me show them the most common words they don't yet know.
Using the app feels odd at first - after learning just a few words, you can already form sentences like "Why did you do this to me?" These sound complex but use only common words. Unlike Duolingo teaching you "apple" early on, learning the most frequent words first lets you grasp sentence structure immediately, then figure out remaining words from context.
No app is a complete language learning system, this included, but I hope it's a useful supplement to whatever else you're doing to learn a language. One useful supplement to my app is the Pimsleur method, which I have been using as well and having a lot of success with.
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on Apple platforms, the app requires the latest version of Safari because I use some APIs that were only recently implemented on Apple platforms. Desktop users are always fine with Chrome of course, regardless of platform. I've considered fixing this, but it would kind of be a pain, and because I'm primarily making the app for myself I haven't put too much effort into things that would not benefit me.
david927•4mo ago
ChadNauseam•4mo ago
The app "only" includes about the 3,000 most common words, so if you're past that level, I don't know how helpful it will be to you. I can easily extend this in the future, I just need bigger corpus with more data.
yorwba•4mo ago
Also, I'm confused that you say you would need a bigger corpus for more words, since your readme says that you use the OpenSubtitles data from OPUS. Their 2024 release has tens of millions of sentences for each language, which surely should be enough for tens of thousands of unique words?
ChadNauseam•4mo ago
What you say about binary search as a good point. I initially used something more like a straightforward binary search, but the issue is that the ramp up is too quick and beginner users would end up adding a bunch of words that were way too advanced for that level. So I tried to make it less aggressive to avoid overshooting, but I guess that has the opposite issue of it taking longer for advanced users. I’ll think about what I can do about that.
For the corpus, I prefer to use Neri’s sentence lists as they’re much higher quality than opensubtitles. You’d be surprised at the problems it has. So I only use opensubtitles for korean (because Neri’s sentence lists doesn’t have a korean version).
ChadNauseam•4mo ago