Qwen-Audio

---

name: qwen-audio

description: "High-performance audio library with text-to-speech (TTS) and speech-to-text (STT)."

version: "0.0.4"

---

# Qwen-Audio

Overview

Qwen-Audio is a high-performance audio processing library optimized. It delivers fast, efficient TTS and STT with support for multiple models, languages, and audio formats.

Prerequisites

Environment checks

Before using any capability, verify that all items in `./references/env-check-list.md` are complete.

Capabilities

Voice Management

Voices are stored in the `./voices/` directory at the skill root level. Each voice has its own folder containing:

#### Create a Voice

Create a reusable voice profile using VoiceDesign model. The `--instruct` parameter is required to describe the voice style:

uv run --project "/<qwen-audio-skill-path>" python "<qwen-audio-skill-path>/scripts/qwen-audio.py" voice create --text "This is a sample voice reference text." --instruct "A warm, friendly female voice with a professional tone." --id "my-voice-id"

Optional: `--id "my-voice-id"` to specify a custom voice ID.

**Returns (JSON):**

{
  "id": "my-voice-id",
  "ref_audio": "/<qwen-audio-skill-path>/voices/my-voice-id/ref_audio.wav",
  "ref_text": "This is a sample voice reference text.",
  "instruct": "A warm, friendly female voice with a professional tone.",
  "duration": 3.456,
  "sample_rate": 24000,
  "success": true
}

#### List Voices

List all created voice profiles:

uv run --project "/<qwen-audio-skill-path>" python "<qwen-audio-skill-path>/scripts/qwen-audio.py" voice list

**Returns (JSON):**

[
  {
    "id": "my-voice-id",
    "ref_audio": "/<qwen-audio-skill-path>/voices/my-voice-id/ref_audio.wav",
    "ref_text": "This is a sample voice reference text.",
    "instruct": "A warm, friendly female voice with a professional tone.",
    "duration": 3.456,
    "sample_rate": 24000
  }
]

Text to Speech

#### TTS Voice Pre-check (Required)

Before any `tts` generation, always confirm the available voices first:

1. Run `voice list` to check the current voice profiles.

2. If the returned list is empty, stop and ask the user what kind of voice they want to create first. Offer style choices, for example:

- Warm and friendly female narrator

- Deep and steady male broadcast voice

- Young and energetic neutral voice

- Calm and professional customer-service voice

Then run `voice create` only after the user confirms a style.

3. If the returned list is not empty, show the available voice `id` values and ask the user to confirm which one should be used as the `--ref_voice` reference id for generation.

Only run `tts` after this confirmation step is complete.

uv run --project "/<qwen-audio-skill-path>" python "<qwen-audio-skill-path>/scripts/qwen-audio.py" tts --text "hello world" --output "/path/to/save.wav"

**Returns (JSON):**

{
  "audio_path": "/path/to/save.wav",
  "duration": 1.234,
  "sample_rate": 24000,
  "success": true
}

Voice Cloning

Clone any voice using a reference audio sample. Provide the wav file and its transcript:

uv run --project "/<qwen-audio-skill-path>" python "<qwen-audio-skill-path>/scripts/qwen-audio.py" tts --text "hello world" --output "/path/to/save.wav" --ref_audio "sample_audio.wav" --ref_text "This is what my voice sounds like."

ref_audio: reference audio to clone

ref_text: transcript of the reference audio

#### Use a Created Voice

After creating a voice, use it for TTS with the `--ref_voice` parameter. The instruct will be automatically loaded:

uv run --project "/<qwen-audio-skill-path>" python "<qwen-audio-skill-path>/scripts/qwen-audio.py" tts --text "New text to speak" --output "/path/to/save.wav" --ref_voice "my-voice-id" --instruct "Very happy and excited."

Optional: `--instruct` to emotion control.

Automatic Speech Recognition (STT)

uv run --project "/<qwen-audio-skill-path>" python "<qwen-audio-skill-path>/scripts/qwen-audio.py" stt --audio "/sample_audio.wav" --output "/path/to/save.txt" --output-format txt

Test audio: https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-ASR-Repo/asr_en.wav

output-format: "txt" | "ass" | "srt" | "all"

**Returns (JSON):**

{
  "text": "transcribed text content",
  "duration": 10.5,
  "sample_rate": 16000,
  "files": ["/path/to/save.txt", "/path/to/save.srt"],
  "success": true
}