local-tts

name	local-tts
version	1.0.0
description	Local text-to-speech using MLX and Kokoro model
triggers	["local-tts","local tts","generate audio locally","kokoro tts"]
dependencies	["mlx-audio (via uv --with)","pydub (via uv --with)"]

Local TTS Skill

Generate high-quality speech audio locally using Apple Silicon MLX acceleration and the Kokoro-82M model. No API keys or recurring costs.

Quick Start

# Generate MP3 from text
uv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \
    --text "Hello, this is a test." \
    --output ~/Desktop/test.mp3

# Generate from file
uv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \
    --file /tmp/script.txt \
    --voice af_heart \
    --output ~/Desktop/podcast.mp3

# List available voices
uv run --with mlx-audio skills/local-tts/scripts/list_voices.py

Parameters

Parameter	Required	Default	Description
--text	One of text/file	-	Text to convert
--file	One of text/file	-	Path to text file
--voice	No	af_heart	Voice preset
--output	Yes	-	Output file path (.mp3, .wav)
--model	No	Kokoro-82M-bf16	Model to use
--list-voices	No	-	Show available voices

Voice Presets

American English Female (prefix: af_)

• af_heart - Warm, friendly (default)
• af_bella - Soft, calm
• af_nova - Clear, professional
• af_river - Clear, confident
• af_sarah - Soft, expressive

American English Male (prefix: am_)

• am_adam - Clear, professional
• am_echo - Deep, smooth
• am_liam - Articulate, conversational
• am_michael - Soft, measured

British English (prefix: bf_, bm_)

• bf_emma - Clear, refined female
• bm_daniel - Clear, professional male
• bm_george - Distinguished male

See references/voices.md for full list.

Output Format

{
  "success": true,
  "file": "/Users/hagelk/Desktop/podcast.mp3",
  "voice": "af_heart",
  "model": "Kokoro-82M-bf16",
  "characters": 9824,
  "chunks": 20,
  "duration_seconds": 612.5,
  "generation_time": 45.2
}

Performance

Hardware	Speed	Notes
M3 Pro 36GB	~3-4x realtime	First run slower (model loading)
M1/M2 Mac Mini 8GB	~1.5x realtime	Works well for briefings
M1/M2 Mac Mini 16GB	~2x realtime	Comfortable headroom

Technical Details

• Model: Kokoro-82M-bf16 (~200MB download on first run)
• Sample rate: 24kHz mono
• Chunking: Text split at ~400 chars per chunk for quality
• Concatenation: Chunks joined seamlessly via pydub
• Formats: MP3, WAV, M4A, OGG

Important Notes

1. MUST use --with flags - Do not use PEP 723 inline deps. mlx-audio requires uv's cached environment.

2. First run is slower - Model downloads ~200MB and espeak dependencies initialize.

3. Model cached at: ~/.cache/huggingface/hub/models--mlx-community--Kokoro-82M-bf16/

Integration with Morning Briefing

The morning-briefing skill uses this for podcast generation:

uv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \
    --file /tmp/morning_briefing_podcast.txt \
    --voice af_heart \
    --output ~/Desktop/morning_briefing.mp3