englishcat
Joined 11 months ago
Joined 11 months ago
What's your next steps, do you plan to add more details of the reflow process?
it sounds like you are at a more advanced stage of learning Chinese, you have moved past simple vocab building and are focusing on flow and fluency reading. For your use case, that 'inverse' approach (Chinese with English safety nets) is definitely superior for pattern-matching, it's a different problem set, but a very valid one.
Appreciate your feedback.
On the other hand, the Chinese writing system is logographic (or ideographic), unlike the English system which is phonetic. The most basic characters, such as 日 (sun), 月 (moon), and 山 (mountain), are essentially graphics (or pictures) of the objects themselves. that makes them very suitable for being represented by images. The emoji you are using is also very good.
I believe this method should be very effective for beginners in Chinese. However, once you have mastered the basic Chinese characters, you can learn about the structure of Chinese characters and then continue reading more materials to expand your vocabulary.
The real challenge is to expand your vocabulary through extensive reading, i'm actually working on a tool to solve this specific problem (https://lingoku.ai/learn-chinese), If you are reading English, it will insert Chinese text for you, if your are reading Chinese text, it will translate the text from Chinese to English then inject Chinese words into the translated text, thus improving your vocabulary while reading.
I’ve just updated the website to be more precise: we use enterprise-grade APIs where they said data is not used for training by default, and we don't log any original content on our own servers.
We also only send the specific text snippets needed for processing to minimize exposure. I really appreciate the feedback, it helps make the project better!
At the moment, Lingoku browser extension does send text to LLms for processing, we don't sell user data, but i agree that simply saying 'trust us' isn't sufficient.
Supporting local LLM is something we are actively considering, though there are still real constraints on the user experience.