Super Auto Talk Tts

Auto-Talk-TTS Skill

Overview

Automatically speaks every message you generate using Microsoft Edge's neural TTS service. Runs asynchronously in the background so your conversation continues immediately while audio generates.

Quick Start

Every message you send is automatically spoken aloud.

The skill wraps your output with auto-speak which:

1. Installs node-edge-tts if needed
2. Converts your message to speech asynchronously
3. Plays the audio in the background
4. Continues your conversation immediately

Usage

Automatic: Every message is auto-spoken. No action needed from you.

Manual override: If you need to speak something specific:

auto-speak "Your text here"

How It Works

1. Detect output: When you generate a message
2. Wrap with auto-speak: The message gets passed through the auto-speak wrapper
3. Install if needed: First run installs node-edge-tts package
4. Generate audio: Convert text to MP3 in background
5. Play audio: Use afplay to play the audio file
6. Continue: Your conversation flows without waiting for audio

Configuration

Edit config.json to customize:

{
  "voice": "en-US-MichelleNeural",
  "rate": "default",
  "pitch": "default",
  "volume": "default",
  "summaryLength": 100
}

Options:

• voice: Any Edge neural voice (see edge-tts skill for full list)
• rate: Speech speed (-20% to +50%, or default)
• pitch: Voice pitch (-20Hz to +20Hz, or default)
• volume: Audio volume (-100% to +100%, or default)
• summaryLength: How many characters to summarize (default: 100)

Installation

First run will automatically install node-edge-tts:

npm install -g node-edge-tts

Or use the bundled installer:

cd /Users/stefano/.openclaw/workspace/skills/auto-talk-tts
npm install

Files

auto-speak

Wrapper script that:

• Checks if node-edge-tts is installed
• Installs it if needed
• Converts text to speech asynchronously
• Plays audio with afplay
• Continues immediately

config.json

User configuration for voice, rate, pitch, volume settings.

package.json

NPM package with node-edge-tts dependency.

SKILL.md

This file.

Integration with SOUL.md

Add this line to the top of your SOUL.md:

## MUST SPEAK WITH TTS EVERY TIME (ASYNCHRONOUSLY)

**I must use the edge-tts skill to convert my response to speech before sending it to you.** Every single message I send must be spoken aloud using the tts tool. This is non-negotiable - I speak to you, I don't just type.

**Async approach:** I run the TTS command in the background using `&` or `nohup` so the conversation continues immediately while audio generates in the background.

Workflow

Automatic (Recommended)

1. You generate a message
2. auto-speak wraps it: The message gets passed through the wrapper
3. Background TTS: Audio generates in background process
4. Immediate reply: Your conversation continues without waiting
5. Audio plays: User hears your response

Manual (If needed)

# Auto-speak any text
auto-speak "Your message here"

# Custom voice
auto-speak "Your message" --voice en-GB-RyanNeural

# Custom speed
auto-speak "Your message" --rate +20%

Testing

# Test the auto-speak wrapper
auto-speak "This is a test. If you can hear this, it's working!"

# Check if node-edge-tts is installed
npm list -g node-edge-tts

# Install manually if needed
npm install -g node-edge-tts

Troubleshooting

• No audio? Check that node-edge-tts is installed: npm list -g node-edge-tts
• Install needed? First run will auto-install, or run: npm install -g node-edge-tts
• Audio not playing? Check system volume and audio output settings
• Slow? Use async mode - audio generates in background, conversation continues immediately

Notes

• Non-blocking: Conversation flows while audio generates
• No API key: Uses Microsoft Edge's free TTS service
• Neural voices: High-quality, natural-sounding speech
• Multiple voices: See edge-tts skill for full voice list
• Configurable: Customize voice, speed, pitch, volume in config.json
• Automatic installation: First run installs node-edge-tts if missing

See Also

• edge-tts - Core TTS engine
• speak-summary - Alternative auto-speak implementation