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dgellow 5 minutes ago [-]
If you don’t mind sharing, how much does that cost you to integrate the translation API, and the text to speech API you’re using? Just curious as I’ve been thinking about doing something in that area (not anki or translations, but also language learning related).
Great project, and congrats for launching :)
altgans 19 minutes ago [-]
Very cool!
Are you willing to share more technical details?
- Which data sources do you ingest?
- How do you transform and enrich the data? How does your pipeline look?
- What are your key challenges?
- Which tools do you use? What is your 'stack'? (Stanze, wordfreq, Whisper, wn, ...)
Background: I am currently building a multi-lang vocabulary hub for language learning. The goal is to match core words/lemmas to their senses/concepts, and then be able to generate multi-language flash cards.
I am still stuck on the sense alignment and fingerprinting (example: should 'to shop', 'einkaufen', ' alışveriş yapmak' and 'go shopping' point to the same concept of 'shop'?), but in a later stage I want to allow user-submission and data enrichment for IPA, pictograms [1] and audio.
Use-case (the dream): I come back from language class, I input new vocab and I output new Anki cards that work across all my fluent languages.
Currently, I mostly find myself knee-deep in problems of linguistics, NLP, Python and getting an LLM to do exactly what I want. At the same time it is a super fun project, and really makes me feel the joy of programming again. LLMs are magic, time just flies by, and all the random projects I always wanted to do suddenly materialize.
For coding, I mostly use free Gemini and some deepseek-v4-flash via openrouter to keep a tight oversight and understand the problem space. Maybe this slows me down, but agentic code jsut does not align with me. Overall, I haven't spent more than 2 € in total.
So far, surprisingly, the biggest problem is the lack of high-quality, free input data (example: English has the Oxford 5000 words as core vocabulary, but it is difficult to find the same for e.g. Turkish).
2nd place is the lack of high-quality synsets/wordnets (cross-language is mostly incomplete), and the 3rd place is getting LLMs to reliable play to their strength (on paper, a LLM is the perfect tool to provide multi-lang sense equivalents)
I plan to do a full writeup sometimes, but first I need it to work :)
qwertox 26 minutes ago [-]
I like the structure of their privacy policy page [0] and how it appears that they are not data-greedy.
And the site itself is a great idea and implementation, though the font size and family of the ui (not of the actual playback area) has a lot of room for improvement, but those are just minor changes.
I don't know what resolution or display you built this on, but a heads up the initial impression on my 4K monitor is that everything is incredibly tiny.
alder 2 hours ago [-]
To be honest I haven't tested it on a 4K monitor yet, so I am not surprised. There are two controls above the transcript that change the font size and the line spacing, which should help a bit for now. Something to fix, thanks!
jrrv 2 hours ago [-]
Is it possible to add traditional characters for mandarin?
Also the pinyin for 誰/谁 is coming through as shuí, whilst this character has two pronounciations, I believe shéi is the more common one.
alder 1 hours ago [-]
Thanks! Chinese and Japanese as source languages are still experimental, I did my best to support them but I have to rely on people who actually know the language and this kind of feedback is really useful. I'll look into adding traditional characters and fixing the pinyin.
jrrv 1 hours ago [-]
No worries, I appreciate the effort. I did go back and listen and they are indeed pronouncing sheí in the audio too.
Although there are some clashes that it does not handle, e.g. 隻 and 只 are both 只 in simplified, you just have to know which one it is from context, but the extension fails to convert to 隻 where appropriate.
3stacks 2 hours ago [-]
This is awesome! I’ll be lurking for new data sources. I’m working on a self-hosted language app more focused around cloze and sentence mining into Anki. I love seeing more stuff happening in this space
alder 2 hours ago [-]
Thanks! I am glad you like it! I essentially mine the source audio, and all examples have cloze style gaps (blurring, in my case) that are revealed on the back of the card. I also beep the word in the sentence when you try to play it on the front card in built-in SRS system. Unfortunately that is not implemented in the Anki export, but it is technically possible.
jcg591 1 hours ago [-]
Very cool! I'm also learning Greek and it's amazing how many resources are becoming available.
alder 1 hours ago [-]
Thanks! Yes, it's getting better for Greek but still not on par with other languages. I completed the only 2 Greek levels on Duolingo and they are really boring compared to the German one I am doing now. Easy Greek is a bit above my level, and the number of YouTubers in Greek is tiny compared to German.
Koaisu 2 hours ago [-]
Just tried it with an unsupported language and it still worked I set it to Chinese and inputted the audio. Still got correct results.
alder 14 minutes ago [-]
Yes, the transcriber API I use (Soniox) actually supports more than 60 languages. I just didn't have any automated testing for them. The way I tested was to find audio with a reliable reference transcription and put it through my pipeline. Then compare the results. Also some languages don't have reliable libraries to get part of speech and lemmas, something that flashcard needs.
pzagor2 58 minutes ago [-]
I also built a tool to help me study Spanish. I really like the idea of shadowing, so I built a tool that lets you take any YouTube video and generate a sentence-by-sentence exercise to help you repeat the speaker's phrases.
Stuff I need to work on:
- It only works with videos that have auto-generated captions
- It works best with monologue videos
47 minutes ago [-]
deaton 46 minutes ago [-]
This is really cool, just as I'm starting to get towards the back end of the Kaishi 1.5k deck so this will be perfect for my Japanese studies. Thanks for sharing.
alder 5 minutes ago [-]
Thanks, I hope it will be helpful! If anything looks off, please let me know.
dirteater_ 2 hours ago [-]
What are you doing for Chinese word segmentation/pinyin?
alder 48 minutes ago [-]
For segmentation and POS I rely on spaCy zh_core_web_sm, pinyin from pypinyin library. Also the small correction level on top. But I am not a Chinese language expert to judge if it really works and I'll rely on feedback from the users to improve it.
hiAndrewQuinn 2 hours ago [-]
Very nice work. I'm going for a different thing, but my audio2anki tool [1] is about as streamlined as I could make it to turn a YouTube URL I want to learn into a stack of Anki flashcards, purely locally.
Great project, and congrats for launching :)
Are you willing to share more technical details?
- Which data sources do you ingest?
- How do you transform and enrich the data? How does your pipeline look?
- What are your key challenges?
- Which tools do you use? What is your 'stack'? (Stanze, wordfreq, Whisper, wn, ...)
Background: I am currently building a multi-lang vocabulary hub for language learning. The goal is to match core words/lemmas to their senses/concepts, and then be able to generate multi-language flash cards.
I am still stuck on the sense alignment and fingerprinting (example: should 'to shop', 'einkaufen', ' alışveriş yapmak' and 'go shopping' point to the same concept of 'shop'?), but in a later stage I want to allow user-submission and data enrichment for IPA, pictograms [1] and audio.
[1: https://arasaac.org/pictograms/search]
Use-case (the dream): I come back from language class, I input new vocab and I output new Anki cards that work across all my fluent languages.
Currently, I mostly find myself knee-deep in problems of linguistics, NLP, Python and getting an LLM to do exactly what I want. At the same time it is a super fun project, and really makes me feel the joy of programming again. LLMs are magic, time just flies by, and all the random projects I always wanted to do suddenly materialize.
For coding, I mostly use free Gemini and some deepseek-v4-flash via openrouter to keep a tight oversight and understand the problem space. Maybe this slows me down, but agentic code jsut does not align with me. Overall, I haven't spent more than 2 € in total.
So far, surprisingly, the biggest problem is the lack of high-quality, free input data (example: English has the Oxford 5000 words as core vocabulary, but it is difficult to find the same for e.g. Turkish).
2nd place is the lack of high-quality synsets/wordnets (cross-language is mostly incomplete), and the 3rd place is getting LLMs to reliable play to their strength (on paper, a LLM is the perfect tool to provide multi-lang sense equivalents)
I plan to do a full writeup sometimes, but first I need it to work :)
And the site itself is a great idea and implementation, though the font size and family of the ui (not of the actual playback area) has a lot of room for improvement, but those are just minor changes.
[0] https://lingochunk.com/privacy
Also the pinyin for 誰/谁 is coming through as shuí, whilst this character has two pronounciations, I believe shéi is the more common one.
I use a firefox extension to convert simplified to traditional, looks like it's open source so that may be of some use to you: https://github.com/tongwentang/tongwentang-extension.
Although there are some clashes that it does not handle, e.g. 隻 and 只 are both 只 in simplified, you just have to know which one it is from context, but the extension fails to convert to 隻 where appropriate.
https://talkhabit.com/shadow Or example, of one exercise: https://talkhabit.com/shadow?videoUrl=https%3A%2F%2Fwww.yout...
Stuff I need to work on: - It only works with videos that have auto-generated captions - It works best with monologue videos
[1]: https://github.com/hiAndrewQuinn/audio2anki