Original Summary

https://lutgaru.com/Sinsajo/ I’ve been trying to improve my English lately and needed a solid transcription tool to get feedback on my speech, basically to check if what I’m saying actually makes sense or is easy to understand. I looked around online, but everything I found were web subscription services that not only charge a monthly fee but also harvest your data. The closest thing to self-hosted was Whisper, but I couldn't find a decent client for it. So, I decided to build my own. Features: Real-time transcription with live text display Multi-platform client (Android, iOS, Desktop) built with Flutter Target language selection with on-the-fly translation (Canary 180M Flash supports EN/ES/FR/DE/PT; Parakeet TDT is English-only) Session audio recording (WAV/OGG) saved on the server It's beneficial for anyone who needs accurate transcription without handing their voice data to third parties journalists, clinicians, developers, or privacy-conscious users. Deployment: Sinsajo has two released components that work together, a Rust server that does the transcription and a Flutter client that captures your microphone and displays the text. How it works: the Flutter client records audio and runs Silero VAD on-device to detect speech, then streams only the speech audio over WebSocket to the Rust server. The server transcribes it locally with an ONNX model and streams the text back to the client in real time. You have two ways to run the server: Docker: pull lutgaru/sinsajo-server and run it with the provided docker-compose.yml (persistent model and records volumes). Native executable: Download the precompiled executables for Linux or Windows, or build the project directly using Cargo. For the client, you don't even need to install anything — there's a web app version available instantly at https://lutgaru.com/Sinsajo/app/ . If you prefer, you can also build and run the native Flutter app ( flutter pub get → flutter run ) and point it at your server's LAN IP. For the full setup, all CLI arguments, Docker Compose examples, and step-by-step usage/troubleshooting, everything is documented in the README at https://github.com/lutgaru/Sinsajo or in the webpage https://lutgaru.com/Sinsajo/ . AI Involvement: The transcription and voice-activity-detection functionality is built on real ML models (Canary 180M Flash / Parakeet TDT 0.6B via transcribe-rs /ONNX Runtime, and Silero VAD v5). AI was used as a development aid for writing and organizing parts of the documentation/README and assisting with code, but the core application logic, architecture, and models are hand-built. No AI-generated content is presented to end users as transcribed output — that comes entirely from the local models.   submitted by   /u/lutgaru [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/17 11:17:56