qwen-audio

Generate speech with voice cloning and transcribe audio to TXT, SRT, or ASS formats.

Updated Jan 13, 2026
One-click install
npx skills add https://github.com/skills-router/skills-store --skill qwen-audio
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: qwen-audio
Source: https://github.com/skills-router/skills-store/tree/main/skills/qwen-audio
Command: npx skills add https://github.com/skills-router/skills-store --skill qwen-audio

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires mlx-audio, qwen-asr, qwen-tts, torch, soundfile, numpy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the need for high-quality, efficient audio processing, enabling users to generate speech from text and transcribe spoken audio with advanced AI models.

Core Features & Use Cases

  • Text-to-Speech (TTS): Generate natural-sounding speech with voice cloning and custom voice creation capabilities.
  • Speech-to-Text (STT): Transcribe audio files into text with support for various output formats (TXT, SRT, ASS).
  • Use Case: A content creator can use TTS to generate voiceovers for videos, and STT to automatically create subtitles from existing audio recordings.

Quick Start

Use the qwen-audio skill to convert the text 'Hello, world!' into an audio file named 'output.wav'.

Frequently Asked Questions about qwen-audio

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I transcribe audio to text with SRT or ASS subtitle formats?

Speech-to-text transcription converts audio files into text with support for multiple output formats including TXT, SRT, and ASS. Using Qwen models, it processes spoken audio to generate formatted text transcripts for subtitle creation.

Can I use text-to-speech with voice cloning to generate custom voiceovers?

Text-to-speech with voice cloning generates natural-sounding speech from text using Qwen models. It supports custom voice creation, allowing you to produce AI voiceovers for audio files like WAV without recording original audio.

Do I need Python 3.10 and specific ML libraries to run Qwen audio models?

Yes, Qwen audio processing requires Python 3.10 or higher and platform-specific ML libraries. Dependencies include mlx-audio, torch, soundfile, and numpy to execute the underlying text-to-speech and speech-to-text models.

What is the best way to create subtitles from existing audio recordings?

The best way to create subtitles from audio recordings is using speech-to-text transcription with Qwen models. It automatically transcribes spoken audio into text and outputs subtitle formats like SRT and ASS for direct video integration.

Does mlx-audio support generating WAV files from text input?

Yes, mlx-audio supports generating audio files from text input. Combined with Qwen text-to-speech capabilities, it processes text strings to synthesize speech and outputs the resulting audio into standard file formats like WAV.