Qwen3 Audio

Qwen3-Audio

Overview

Qwen3-Audio is a high-performance audio processing library optimized for Apple Silicon (M1/M2/M3/M4). It delivers fast, efficient TTS and STT with support for multiple models, languages, and audio formats.

Prerequisites

• Python 3.10+
• Apple Silicon Mac (M1/M2/M3/M4)

Environment checks

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

Capabilities

Text to Speech

uv run --python ".venv/bin/python" "./scripts/mlx-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
}

Voice Cloning

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

uv run --python ".venv/bin/python" "./scripts/mlx-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 Created Voice (Shortcut)

Use a voice created with voice create by its ID:

uv run --python ".venv/bin/python" "./scripts/mlx-audio.py" tts --text "hello world" --output "/path_to_save.wav" --ref_voice "my-voice-id"

This automatically loads ref_audio and ref_text from the voice profile.

CustomVoice (Emotion Control)

Use predefined voices with emotion/style instructions:

uv run --python ".venv/bin/python" "./scripts/mlx-audio.py" tts --text "hello world" --output "/path_to_save.wav" --speaker "Ryan" --language "English" --instruct "Very happy and excited."

VoiceDesign (Create Any Voice)

Create any voice from a text description:

uv run --python ".venv/bin/python" "./scripts/mlx-audio.py" tts --text "hello world" --output "/path_to_save.wav" --language "English" --instruct "A cheerful young female voice with high pitch and energetic tone."

Automatic Speech Recognition (STT)

uv run --python ".venv/bin/python" "./scripts/mlx-audio.py" stt --audio "/sample_audio.wav" --output "/path_to_save.txt" --output-format srt

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"]
}

Voice Management

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

• ref_audio.wav - Reference audio file
• ref_text.txt - Reference text transcript
• ref_instruct.txt - Voice style description

Create a Voice

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

uv run --python ".venv/bin/python" "./scripts/mlx-audio.py" voice create --text "This is a sample voice reference text." --instruct "A warm, friendly female voice with a professional tone." --language "English"

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

Returns (JSON):

{
  "id": "abc12345",
  "ref_audio": "/path/to/skill/voices/abc12345/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
}

List Voices

List all created voice profiles:

uv run --python ".venv/bin/python" "./scripts/mlx-audio.py" voice list

Returns (JSON):

[
  {
    "id": "abc12345",
    "ref_audio": "/path/to/skill/voices/abc12345/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
  }
]

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 --python ".venv/bin/python" "./scripts/mlx-audio.py" tts --text "New text to speak" --output "/output.wav" --ref_voice "abc12345"

Predefined Speakers (CustomVoice)

For Qwen3-TTS-12Hz-1.7B/0.6B-CustomVoice models, the supported speakers and their descriptions are listed below. We recommend using each speaker's native language for best quality. Each speaker can still speak any language supported by the model.

Released Models