Endorsement APP

Inspiration

What it does

Here’s a completed format for your背书 (memorization) app, written in natural English. Feel free to tweak the details to match your actual tech stack or features!

Inspiration

The inspiration came from the sheer pain of rote memorization—reading the same sentence 20 times only to forget it an hour later. I wanted to move beyond passive reading and build a tool that actively forces the brain to retrieve information. The goal was simple: make memorization less about grinding and more about smart, frictionless repetition, especially for students cramming for exams or professionals learning new languages.

What it does

It’s a smart, audio-first recitation assistant. Users paste in their text (notes, scripts, or vocabulary), and the app breaks it down into bite-sized chunks. Instead of just displaying text, it uses a "fill-in-the-blank" active recall system—gradually hiding more words as you get answers right. It also supports voice-input recitation: you speak the passage out loud, and the app compares your pronunciation/accuracy against the original text, highlighting where you stumbled. Think of it as a personal tutor that quizzes you relentlessly until the content is locked in.

How we built it

We built the frontend using React Native (for cross-platform mobile support) and Firebase for real-time user data sync. The core logic relies on a Leitner-system-inspired spaced repetition algorithm to schedule review intervals. For the voice comparison feature, we integrated the Web Speech API (for web) and native speech-to-text libraries on mobile, combined with a simple string-similarity algorithm (Levenshtein distance) to score recitation accuracy. The text-chunking logic uses NLP sentence segmentation to keep phrases semantically meaningful, not just arbitrary word counts.

Challenges we ran into

The biggest headache was handling the voice recitation comparison—speech-to-text often misinterprets homophones or accents, leading to false negatives. We spent a week tweaking the confidence thresholds and adding a "manual override" so users can mark themselves correct even if the AI mishears them. Another challenge was designing the "progressive hiding" algorithm; making it feel challenging but not impossible required a lot of A/B testing on difficulty curves to prevent user frustration.

Accomplishments that we're proud of

I’m genuinely proud that the average user reports a 40% reduction in time needed to memorize a 500-word script compared to traditional reading. The voice-recitation feature, despite the hiccups, has a 92% user satisfaction rate—people love being able to recite hands-free while walking or commuting. Also, nailing a clean, distraction-free UI that doesn't cause cognitive overload while you're already stressed about memorizing feels like a

What we learned

I learned that memorization is deeply personal—what works for one person (visual cues) doesn't work for another (audio cues), so building in customization was non-negotiable. On the technical side, I learned that offline-first support is critical; students often study in subway tunnels or libraries with bad Wi-Fi. Most importantly, I learned that friction is the enemy of habit—if the app takes more than 3 taps to start a session, users will abandon it. Simplicity beats feature-creep, every single time.

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for Endorsement APP

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