LaunchKit · 2026
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qwenspeak

Text-to-speech generation via Qwen3-TTS over SSH.

0
585 downloads
by @psyb0t

Setup & Installation

openclaw skills install @psyb0t/qwenspeak

Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:

npx clawhub install qwenspeak

Version History

v1.5.0Feb 17, 2026 - Version note by skill developer:

**This release introduces a setup guide and major documentation updates.** - Added dedicated installation and deployment instructions in references/setup.md. - Simplified and clarified the main documentation, removing redundant detail. - Job handling is now explicitly sequential (one at a time, queued). - Job status terminology updated: jobs start as "queued" instead of "pending". - Documentation improved for file operations, YAML options, and parameters. - Housekeeping details added: jobs now auto-cleaned (1 day for completed, 1 week for all).

What This Skill Does

YAML-driven text-to-speech over SSH using Qwen3-TTS models. Supports three modes: preset voices, voice design from natural language descriptions, and voice cloning from reference audio. Jobs are submitted as YAML configs, run sequentially, and output WAV files.

Runs on self-hosted infrastructure via SSH, keeping audio data private and avoiding per-request cloud TTS costs.

When to use it

  • Generating narration for tutorial or explainer videos
  • Cloning a specific person's voice for consistent audio content
  • Batch-producing dialogue lines for a game or animation
  • Designing a custom voice character from a text description
  • Producing multilingual voiceovers from a single YAML workflow

Example Workflow

Here's how your AI assistant might use this skill in practice.

INPUT

User asks: clone my voice from a reference recording and read out a three-line script

AGENT
  1. 1Upload the reference audio file using 'put refs/me.wav'
  2. 2Write a YAML job with voice-clone mode, setting ref_audio to refs/me.wav and ref_text to the transcript
  3. 3Submit the job via the 'tts' command and capture the returned job UUID
  4. 4Poll job status with 'tts get-job <uuid>' until status reaches completed
  5. 5Download each output WAV file using 'get <output_path>'
OUTPUT

WAV files with the cloned voice reading each line of the script

Requirements

Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.

QWENSPEAK_HOST environment variableQWENSPEAK_PORT environment variableRunning qwenspeak instance (self-hosted via https://github.com/psyb0t/docker-qwenspeak)