Local STT (Nvidia Parakeet + Whisper Support)

Local STT with selectable backends - Parakeet (best accuracy) or Whisper (fastest, multilingual).

Local STT (Parakeet / Whisper)

Unified local speech-to-text using ONNX Runtime with int8 quantization. Choose your backend:

• Parakeet (default): Best accuracy for English, correctly captures names and filler words
• Whisper: Fastest inference, supports 99 languages

Usage

bash

# Default: Parakeet v2 (best English accuracy)
~/.openclaw/skills/local-stt/scripts/local-stt.py audio.ogg

# Explicit backend selection
~/.openclaw/skills/local-stt/scripts/local-stt.py audio.ogg -b whisper
~/.openclaw/skills/local-stt/scripts/local-stt.py audio.ogg -b parakeet -m v3

# Quiet mode (suppress progress)
~/.openclaw/skills/local-stt/scripts/local-stt.py audio.ogg --quiet

Options

• -b/--backend: parakeet (default), whisper
• -m/--model: Model variant (see below)
• --no-int8: Disable int8 quantization
• -q/--quiet: Suppress progress
• --room-id: Matrix room ID for direct message

Models

Parakeet (default backend)

Model	Description
v2 (default)	English only, best accuracy
v3	Multilingual

Whisper

Model	Description
tiny	Fastest, lower accuracy
base (default)	Good balance
small	Better accuracy
large-v3-turbo	Best quality, slower

Benchmark (24s audio)

Backend/Model	Time	RTF	Notes
Whisper Base int8	0.43s	0.018x	Fastest
Parakeet v2 int8	0.60s	0.025x	Best accuracy
Parakeet v3 int8	0.63s	0.026x	Multilingual

openclaw.json

json

{
  "tools": {
    "media": {
      "audio": {
        "enabled": true,
        "models": [
          {
            "type": "cli",
            "command": "~/.openclaw/skills/local-stt/scripts/local-stt.py",
            "args": ["--quiet", "{{MediaPath}}"],
            "timeoutSeconds": 30
          }
        ]
      }
    }
  }
}