parakeet

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)

1. Parakeet Dictate repo at ~/Programming/parakeet-dictate/ with Python venv
2. Install dependencies:

   cd ~/Programming/parakeet-dictate
   uv venv && uv pip install -r requirements.txt
   

3. (Optional) Set custom path: export PARAKEET_HOME=/path/to/parakeet-dictate

Implementation

When this skill is invoked:

1. For audio files: Run the transcription script

   cd ~/.claude/skills/parakeet/scripts && \
   ${PARAKEET_HOME:-~/Programming/parakeet-dictate}/.venv/bin/python transcribe.py "<filepath>"
   

2. For live dictation: Run the dictation script

   cd ~/.claude/skills/parakeet/scripts && \
   ${PARAKEET_HOME:-~/Programming/parakeet-dictate}/.venv/bin/python dictate.py
   

3. 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