| name | parakeet |
| description | Local speech-to-text via Handy app (push-to-talk) and NeMo CLI scripts. Parakeet V3: 25 languages, auto-detection, ~30x realtime on M4 Max, 6% WER. This skill should be used when transcribing audio files or dictating voice input.
|
| argument-hint | ["audio-file | \"dictate\" | \"check\""] |
| tools | ["Bash","Read","Write"] |
Parakeet Dictation Skill
Local speech-to-text powered by NVIDIA Parakeet TDT 0.6B V3 (~600MB model, 100% offline).
Two Modes
1. Handy App (Primary — Push-to-Talk into Any Text Field)
Handy is a free, open-source Tauri app (Rust + React) providing
push-to-talk dictation with Parakeet V3 built in. Inference via
transcribe-rs (ONNX Runtime, int8 quantized).
brew install --cask handy
- Default hotkey: ⌥Space (Option-Space) on macOS, Ctrl-Space on Windows/Linux
- Modes: Push-to-talk (hold) or toggle (press to start/stop)
- Select Parakeet V3 in Settings → Models (auto-downloads ~478MB)
- Grant microphone + accessibility permissions
- Includes VAD (Silero), model management UI
- Additional models: Whisper (Small/Medium/Turbo/Large), Moonshine, SenseVoice
- Models stored at
~/Library/Application Support/com.pais.handy/models/
2. CLI Scripts (Claude Code File Transcription & Terminal Dictation)
CLI scripts remain for headless/terminal use within Claude Code. These use NeMo/PyTorch.
Performance
| System | Speed | Engine |
|---|
| Handy (M4 Max) | ~30x realtime | transcribe-rs / ONNX int8 |
| Handy (Zen 3) | ~20x realtime | transcribe-rs / ONNX int8 |
| Handy (Skylake i5) | ~5x realtime | transcribe-rs / ONNX int8 |
| NeMo CLI (MPS) | Varies | NeMo / PyTorch |
- Accuracy: 6.05% WER (Word Error Rate)
- Languages: 25 European languages with automatic detection (no prompting)
- Privacy: 100% local processing, no cloud API
- License: CC BY 4.0 (model), MIT (Handy app)
Commands
Transcribe Audio File
/parakeet path/to/audio.wav
/parakeet ~/recordings/interview.mp3
/parakeet meeting.m4a
Supported formats: .wav, .mp3, .m4a, .flac, .ogg, .aac
Live Dictation (Terminal)
/parakeet
/parakeet dictate
Record from microphone until Enter is pressed, then transcribe.
Check Installation
/parakeet check
Verify Parakeet is properly installed and model can load.
Setup
Handy (Push-to-Talk UI)
brew install --cask handy
Launch from Applications, select Parakeet V3 model, configure hotkey.
CLI Scripts (Prerequisites)
- Parakeet Dictate repo at
~/Programming/parakeet-dictate/ with Python venv
- Install dependencies:
cd ~/Programming/parakeet-dictate
uv venv && uv pip install -r requirements.txt
- (Optional) Set custom path:
export PARAKEET_HOME=/path/to/parakeet-dictate
Implementation
When this skill is invoked:
-
For audio files: Run the transcription script
cd ~/.claude/skills/parakeet/scripts && \
${PARAKEET_HOME:-~/Programming/parakeet-dictate}/.venv/bin/python transcribe.py "<filepath>"
-
For live dictation: Run the dictation script
cd ~/.claude/skills/parakeet/scripts && \
${PARAKEET_HOME:-~/Programming/parakeet-dictate}/.venv/bin/python dictate.py
-
For checking setup: Run the check script
cd ~/.claude/skills/parakeet/scripts && \
${PARAKEET_HOME:-~/Programming/parakeet-dictate}/.venv/bin/python check_setup.py
3. Server Mode (OpenAI-Compatible STT for Takopi)
An OpenAI-compatible transcription server for integration with Takopi and other
API clients. Exposes POST /v1/audio/transcriptions wrapping the NeMo CLI.
uv run --with fastapi,uvicorn,python-multipart \
~/.claude/skills/parakeet/scripts/parakeet_server.py --port 8384
Takopi config (~/.takopi/takopi.toml):
voice_transcription_base_url = "http://localhost:8384/v1"
voice_transcription_api_key = "local"
voice_transcription_model = "parakeet-tdt-0.6b"
Endpoints: /v1/audio/transcriptions (POST, multipart), /v1/models (GET),
/health (GET). Supports response_format: json, text, verbose_json.
Accepts .wav, .mp3, .m4a, .flac, .ogg, .aac, .oga, .webm.
50 MB upload limit. 120s transcription timeout.
Model Caches
| System | Cache Location | Size | Engine |
|---|
| Handy | ~/Library/Application Support/com.pais.handy/models/ | ~478MB | transcribe-rs (ONNX int8) |
| NeMo CLI | ~/.cache/nemo/ | ~1.2GB | NeMo / PyTorch |
Model caches are separate. Handy's Parakeet V3 int8 model structure:
parakeet-tdt-0.6b-v3-int8/
├── encoder-model.int8.onnx
├── decoder_joint-model.int8.onnx
├── nemo128.onnx (audio preprocessor)
└── vocab.txt
Troubleshooting
"No module named nemo"
Use the Parakeet virtual environment. Scripts automatically use the correct Python.
"MPS not available"
Apple Silicon Metal acceleration requires PyTorch 2.0+. Falls back to CPU automatically.
"Permission denied: microphone"
Grant microphone access in System Preferences → Privacy & Security → Microphone.
Model download slow
The Parakeet model downloads on first use (~478MB for Handy, ~1.2GB for NeMo). Subsequent runs use cache.
Configuration
| Variable | Default | Description |
|---|
PARAKEET_HOME | ~/Programming/parakeet-dictate | Parakeet Dictate installation path |
Dependencies
Handy: brew install --cask handy (standalone, no other deps)
CLI scripts require:
- Parakeet Dictate repo at
$PARAKEET_HOME (default: ~/Programming/parakeet-dictate)
- Python virtual environment at
$PARAKEET_HOME/.venv
- NeMo toolkit with ASR support (
nemo_toolkit[asr]>=2.0.0)
- PyTorch 2.0+ (for MPS/CUDA acceleration)
- soundfile and sounddevice for audio handling
