Lango3

Learn new languages through music and AI chatting features

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Inspiration

I often struggled in language-related classes in the U.S. because my native language is neither English nor Spanish. Keeping up meant spending extra time trying to build proficiency, which made learning feel stressful and discouraging at times when I didn't attain the result I hoped for.

At the same time, my experience playing in orchestra showed me how much easier it is to learn when the environment feels engaging and enjoyable with a less stressed focus on getting it right immediately. That contrast inspired me to combine music and language learning into a simple tool that helps others learn more comfortably and avoid the difficulties I experienced.

What it does

A lot of students often don't have time to consistently spend on learning a new language and the way school teaches languages takes a lot of time and effort. Research has proven that music is a powerful tool to effectively learn languages while retaining the knowledge for extended periods*. Lango3 is designed to do just that, as users can listen to songs from different languages and use AI-powered tools to better understand vocabulary, meanings, and language patterns found in the music. Instead of memorization, the app focuses on learning through context and immersion.

How I built it

I built the frontend using React with Vite and TypeScript, focusing on speed and a clean user experience. The backend is written in Python using FastAPI and runs in a serverless setup that works with Vercel.

I used VS Code throughout development and designed the interface in Figma before writing the code. The app also integrates external APIs to support music data and AI-based language explanations.

Challenges I ran into

1- Lyrics copyright restrictions made it impossible to scrape or directly display song lyrics legally. 2- Getting FastAPI to work smoothly in a serverless environment required rethinking parts of the backend. 3- Styling the frontend took longer than expected due to large CSS files generated from Figma designs. 4- Finding APIs that were both reliable and low-latency involved a lot of trial and error. 5- My limited experience with backend development and databases added an extra learning curve.

Accomplishments that I'm proud of

1- Setting up and deploying a fully serverless FastAPI backend. 2- Gaining confidence with TypeScript and frontend structure. 3- Turning an idea into a working product that people can actually use.

What I learned

1- How to build and deploy Apps that use FastAPI. 2- How frontend and backend systems communicate in real-world applications. 3- How to work through technical limitations and adapt designs accordingly.

What's next for Lango3

1- Improve AI prompts for clearer and more helpful explanations. 2- Refine the UI to feel more polished and less plain. 3- Reduce load times and improve overall performance. 4- Add a progress-tracking feature for users. 5- Implement a forgot-password flow. 6- Expand support to more languages.

*Source: https://www.cambridgeschool.com/en/how-music-can-help-you-learn-a-new-language-eng.html

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