Scriberr

Launch the image from the Azure Marketplace into your resource group, and choose your VNet, subnet and SSH key. Open port 80 (HTTP) to the networks that should reach the web interface, and port 22 (SSH) to your admin network.

The first boot prepares the service and creates your administrator. Allow a minute or two after the VM reports running.

There is no default password. The first boot generates a unique administrator credential for your instance and writes it to a root-only file. SSH in and read the file:

sudo cat /root/scriberr-credentials.txt

The file shows the generated username and password and your instance URL:

# Scriberr on Ubuntu 24.04 — Per-VM Credentials (root only) SCRIBERR_ADMIN_USERNAME=admin SCRIBERR_ADMIN_PASSWORD=<ADMIN_PASSWORD> SCRIBERR_URL=http://<your-vm-ip>/

The file has mode 0600, so only root can read it. Self-registration is already closed, so this administrator is the only account. Confirm both:

sudo ls -l /root/scriberr-credentials.txt curl -s http://127.0.0.1/api/v1/auth/registration-status

The registration status returns {"registration_enabled":false}, so no one can register a second account.

Browse to http://<your-vm-ip>/. On the Sign In screen, enter the username and password from the credentials file.

To confirm from the command line that the credential works and that the default admin/admin is rejected, run:

# the per-VM admin authenticates and returns a JWT curl -s -o /dev/null -w 'admin login: HTTP %{http_code}\n' -X POST http://127.0.0.1/api/v1/auth/login \
  -H 'Content-Type: application/json' \
  -d '{"username":"<ADMIN_USERNAME>","password":"<ADMIN_PASSWORD>"}'
# a guessed default credential is refused curl -s -o /dev/null -w 'default admin/admin: HTTP %{http_code}\n' -X POST http://127.0.0.1/api/v1/auth/login \
  -H 'Content-Type: application/json' \
  -d '{"username":"admin","password":"admin"}'

The per-VM login returns 200, and the default admin/admin returns 401.

After you sign in, you land on your recordings dashboard. Click the + button to upload an audio file. Keep the default CPU (Standard_B2s) profile, which uses the baked small model, int8 compute and silero voice activity detection, and start the transcription. Progress streams live. When the transcription completes, the recording appears in the list with a green tick.

Open the recording to read the transcript. Scriberr shows an audio player and the transcript text, with word-level timings available underneath.

The whole flow works offline against the baked model. You can also drive it from the API. The following script transcribes a short clip end to end and prints the transcript:

# log in and capture a JWT
TOKEN=$(curl -s -X POST http://127.0.0.1/api/v1/auth/login -H 'Content-Type: application/json' \
  -d '{"username":"<ADMIN_USERNAME>","password":"<ADMIN_PASSWORD>"}' | python3 -c 'import sys,json;print(json.load(sys.stdin)["token"])')
# submit the bundled sample clip for a quick transcription
JOB=$(curl -s -X POST http://127.0.0.1/api/v1/transcription/quick -H "Authorization: Bearer $TOKEN" \
  -F 'audio=@/opt/scriberr/sample/sample-english.wav;type=audio/wav' \
  -F 'parameters={"model":"small","compute_type":"int8","device":"cpu","vad_method":"silero","diarize":false,"batch_size":4}' \
  | python3 -c 'import sys,json;print(json.load(sys.stdin)["id"])')
# poll until it finishes and print the transcript for i in $(seq 1 40); do
S=$(curl -s http://127.0.0.1/api/v1/transcription/quick/$JOB -H "Authorization: Bearer $TOKEN")
echo "$S" | grep -q '"status":"completed"' && {
echo "$S" | python3 -c 'import sys,json;print(json.load(sys.stdin)["transcript"].strip())'; break; } sleep 3 done

• Higher accuracy: in the transcription profile, choose a larger Whisper model (medium or large-v3). Larger models need more RAM and CPU, so pair them with a larger VM size.
• Speaker diarization: PyAnnote diarization requires a free HuggingFace access token and acceptance of the pyannote model licence. Add your token to a profile and enable diarization to label speakers.
• Summaries and chat: to summarise or chat over a transcript, add an OpenAI-compatible API key in the settings, or point Scriberr at a local model endpoint.