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Scriberr

Self-hosted AI audio transcription with speaker detection, AI chat, and pristine privacy. Fully offline, no data ever leaves your server.

★ 2,840 GitHub MIT audiotranscriptionspeech-to-textwhisperself-hostedprivacygodiarization Image & Video

Overview

Scriberr is an open-source, self-hosted audio transcription application that runs completely offline on your own hardware. Using state-of-the-art ML models like NVIDIA Parakeet, Canary, and Whisper, it delivers high-accuracy transcripts with word-level timing. Key features include automatic speaker detection (diarization), AI chat with your transcripts via Ollama or OpenAI API, a built-in audio recorder, folder watcher for automated processing, and a polished PWA interface working on both desktop and mobile. Built in Go, Scriberr ensures no audio data ever reaches third-party cloud services. Perfect for journalists, researchers, students, and privacy-conscious users who need accurate transcription without subscription fees. Self-host it with a single Docker command and maintain full control over your data.

Requirements

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Affiliate disclosure

Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  scriberr:
    image: testype/scriberr:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/scriberr:/data

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