Hello! I'm excited to introduce "Wake-Up," an open-source React component that can recognize the sound of clapping or finger snapping on the web. 🎉
- MIT License (commercial use allowed): Ready to test with a model size of just 5MB!
🎮 Try It Out Now!
👉 Visit the Demo Page
🔍 GitHub Repository
⚠️ Tips for Better Recognition:
Use an external microphone for the best results.
Earphones or Airpods may not work as well.
Works on both desktop and mobile!
💻 How to Use It?
First, install it:
npm install wake-me
# or
yarn add wake-me
You can easily use it in React like this:
import { WakeMe } from "wake-me";
function App() {
return <WakeMe onSnap={() => console.log("Snap!")} />;
}
🤔 Potential Use Cases
- 🎙️ AI Systems: Wake up AI assistants with a finger snap, just like saying "Hey Siri."
- 🎭 Presentations: Advance slides with a snap.
- 🖥️ Video Conferences: Get attention or a turn to speak.
- 🎨 Digital Art: Interactive exhibitions responding to audience sounds.
- 🤖 Smart Homes: Control IoT devices with claps or finger snaps.
✨ Features of the Library
- 🚀 High-performance AI model implemented with TensorFlow.js.
- ⚡ Real-time sound detection and analysis.
- 🪶 Lightweight and easy-to-use structure.
You can also use it with vanilla JavaScript:
<script src="https://cdn.jsdelivr.net/npm/wake-me@latest/dist/vanilla/vanilla.global.js"></script>
<script>
const wakeMe = new WakeMe({
onSnap: () => console.log("Snap!"),
onNoise: (score) => console.log("Noise level:", score)
});
wakeMe.init();
</script>
🤔 Can It Be Used Commercially?
Yes! This project is provided by the LLAMI Team and is available under the MIT license, so feel free to use it as you like!
😭 Limitations of the Library
The current version is designed for tablet demonstrations, and on devices like MacBooks, it may also pick up sounds such as keyboard typing, tapping on a desk, or chair squeaks. We're working to improve this!
Top comments (5)
great!
I admire your project and have reviewed your profile and the languages you've used. I've noticed you don't have a background in Python. As a web developer interested in learning TensorFlow.js, could you share how you studied TensorFlow and built your foundational knowledge in AI/ML?
best
Congrats!
good project!