SuperAPI AI Directory

local-tts

Office & productivity

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Updated 10-16 06:22

About this skill

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

```json
{
  "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