speakturbo-tts

emzod/speak-turbo · updated Apr 8, 2026

$npx skills add https://github.com/emzod/speak-turbo --skill speakturbo-tts
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summary

Ultra-fast text-to-speech with ~90ms latency and 8 built-in voices.

  • Delivers audio in approximately 90ms after daemon warmup, with first run taking 2-5 seconds for model initialization
  • Includes 8 pre-configured voices (alba, marius, javert, jean, fantine, cosette, eponine, azelma) accessible via simple command-line flags
  • Supports file output with configurable directory allowlisting, quiet mode, and UTF-8 text input including long-form content
  • Auto-starting daemon with 1-hour idle
skill.md

speakturbo - Talk to your Claude!

Give your agent the ability to speak to you real-time. Ultra-fast text-to-speech with ~90ms latency and 8 built-in voices.

Quick Start

# Play immediately - you should hear "Hello world" through your speakers
speakturbo "Hello world"
# Output: ⚡ 92ms → ▶ 93ms → ✓ 1245ms

# Verify it's working by saving to file
speakturbo "Hello world" -o test.wav
ls -lh test.wav  # Should show ~50-100KB file

Output explained: = first audio received, = playback started, = done

First Run

The first execution takes 2-5 seconds while the daemon starts and loads the model into memory. Subsequent calls are ~90ms to first sound.

# First run (slow - daemon starting)
speakturbo "Starting up"  # ~2-5 seconds

# Second run (fast - daemon already running)
speakturbo "Now I'm fast"  # ~90ms

Usage

# Basic - plays immediately (default voice: alba)
speakturbo "Hello world"

# Save to file (no audio playback)
speakturbo "Hello" -o output.wav

# Save to specific file
speakturbo "Goodbye" -o goodbye.wav

# Quiet mode (suppress status messages, still plays audio)
speakturbo "Hello" -q

# List available voices
speakturbo --list-voices

Available Voices

Voice Type
alba Female (default)
marius Male
javert Male
jean Male
fantine Female
cosette Female
eponine Female
azelma Female

Performance

Metric Value
Time to first sound ~90ms (daemon warm)
First run 2-5s (daemon startup)
Real-time factor ~4x faster
Sample rate 24kHz mono

Architecture

speakturbo (Rust CLI, 2.2MB)
    │ HTTP streaming (port 7125)
speakturbo-daemon (Python + pocket-tts)
    │ Model in memory, auto-shutdown after 1hr idle
Audio playback (rodio)

Text Input

  • Encoding: UTF-8
  • Quotes in text: Use escaping: speakturbo "She said \"hello\""
  • Long text: Supported, streams as it generates

Output Path Security

The -o flag only writes to directories that are on the allowlist. By default, these are:

  • /tmp and system temp directories
  • Your current working directory
  • ~/.speakturbo/

If you need to write elsewhere, use --allow-dir:

speakturbo "Hello" -o /custom/path/audio.wav --allow-dir /custom/path

To permanently allow a directory, add it to ~/.speakturbo/config:

mkdir -p ~/.speakturbo && echo "/custom/path" >> ~/.speakturbo/config

The config file is one directory per line. Lines starting with # are comments.

Exit Codes

Code Meaning
0 Success (audio played/saved)
1 Error (daemon connection failed, invalid args)

When to Use

Use speakturbo when:

  • You need instant audio feedback (~90ms)
  • Speed matters more than voice variety
  • Built-in voices are sufficient

Use speak instead when:

  • You need custom voice cloning (Morgan Freeman, etc.) → speak "text" --voice ~/.chatter/voices/morgan_freeman.wav
  • You need emotion tags like [laugh], [sigh]
  • Quality/variety matters more than speed

See the speak skill documentation for full usage.

Troubleshooting

No audio plays:

# Check daemon is running
curl http://127.0.0.1:7125/health
# Expected: {"status":"ready","voices":["alba","marius",...]}

# Verify by saving to file and playing manually
speakturbo "test" -o /tmp/test.wav
afplay /tmp/test.wav  # macOS
aplay /tmp/test.wav   # Linux

Daemon won't start:

# Check port availability
lsof -i :7125

# Manually kill and restart
pkill -f "daemon_streaming"
speakturbo "test"  # Auto-restarts daemon

First run is slow: This is expected. The daemon needs to load the ~100MB model into memory. Subsequent calls will be fast (~90ms).

Daemon Management

The daemon auto-starts on first use and auto-shuts down after 1 hour idle.

# Check status
curl http://127.0.0.1:7125/health

# Manual stop
pkill -f "daemon_streaming"

# View logs
cat /tmp/speakturbo.log

Comparison with speak

Feature speakturbo speak
Time to first sound ~90ms ~4-8s
Voice cloning
Emotion tags
Voices 8 built-in Custom wav files
Engine pocket-tts Chatterbox

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.474 reviews
  • William Ndlovu· Dec 20, 2024

    speakturbo-tts reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Luis Robinson· Dec 20, 2024

    Keeps context tight: speakturbo-tts is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Luis Jackson· Dec 20, 2024

    Registry listing for speakturbo-tts matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Kofi Shah· Dec 20, 2024

    speakturbo-tts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Camila Haddad· Dec 16, 2024

    Registry listing for speakturbo-tts matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Daniel Kim· Dec 16, 2024

    Solid pick for teams standardizing on skills: speakturbo-tts is focused, and the summary matches what you get after install.

  • Chaitanya Patil· Dec 12, 2024

    speakturbo-tts has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Arjun Sharma· Dec 12, 2024

    Useful defaults in speakturbo-tts — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Mei Gupta· Dec 4, 2024

    Useful defaults in speakturbo-tts — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Anaya Verma· Dec 4, 2024

    I recommend speakturbo-tts for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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