{"slug": "birdecho-discover-birds-around-you-with-open-source-ai", "title": "BirdEcho: Discover Birds Around You with Open-Source AI 🐦", "summary": "A developer built BirdEcho, an open-source web app that identifies bird species from recorded audio using the BirdNET+ V3.0 model running entirely in the browser via ONNX Runtime Web and WebAssembly. To keep the interface responsive while running a large model client-side, the developer used Web Workers for inference and split the model into smaller downloadable chunks, so recordings never leave the user's device. The code is released under MIT, while the BirdNET+ model carries its own CC BY-SA 4.0 license and additional usage restrictions.", "body_md": "*This is a submission for the [Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass](https://dev.to/challenges/hacktoberfest-week1-2026-10-05).*\n\nI built **BirdEcho**, an AI-powered bird sound identification app that encourages people to step outside and explore nature.\n\nEver heard a bird singing and wondered what species it was? With BirdEcho, you can record its sound and let AI identify it.\n\nThe app also lets you:\n\nThe goal is simple: **less scrolling, more exploring!**\n\n🌐 **Live App:** [https://birdecho.pages.dev](https://birdecho.pages.dev)\n\nOpen the app, record a bird singing, or use the built-in sample to try bird identification.\n\n💻 **GitHub:** [https://github.com/shadowe1ite/birdecho](https://github.com/shadowe1ite/birdecho)\n\nThe complete source code is publicly available, including setup instructions and model documentation.\n\nI built BirdEcho using **React, Vite, BirdNET+, and ONNX Runtime Web**.\n\nBirdEcho uses the BirdNET+ V3.0 model to recognize bird sounds. Audio is processed directly in the browser using WebAssembly, without sending recordings to an AI server.\n\nThe app uses:\n\nOne challenge was running a large AI model inside the browser while keeping the app responsive. I used Web Workers to handle inference and split the model into smaller downloadable chunks.\n\nOpenly available AI models made BirdEcho possible without depending on paid AI APIs.\n\nBy running AI locally, BirdEcho can identify birds without uploading their recordings to external inference services.\n\nThe application's code is open source under MIT, while the BirdNET+ model has its own CC BY-SA 4.0 license and additional usage restrictions.\n\nI believe AI shouldn't always keep us glued to screens. Sometimes, it should encourage us to explore the world around us.\n\n**That's the idea behind BirdEcho.** 🌿🐦", "url": "https://wpnews.pro/news/birdecho-discover-birds-around-you-with-open-source-ai", "canonical_source": "https://dev.to/shadowe1ite/birdecho-discover-birds-around-you-with-open-source-ai-394i", "published_at": "2026-10-11 19:55:05+00:00", "updated_at": "2026-10-11 20:02:20.253067+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "ai-tools", "developer-tools"], "entities": ["BirdEcho", "BirdNET+", "ONNX Runtime Web", "React", "Vite", "GitHub", "Hacktoberfest"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/birdecho-discover-birds-around-you-with-open-source-ai", "markdown": "https://wpnews.pro/news/birdecho-discover-birds-around-you-with-open-source-ai.md", "text": "https://wpnews.pro/news/birdecho-discover-birds-around-you-with-open-source-ai.txt", "jsonld": "https://wpnews.pro/news/birdecho-discover-birds-around-you-with-open-source-ai.jsonld"}}