By name: qwen-asr-skill description: Local speech-to-text transcription using Qwen3-ASR-1.7B. Use this skill when a user provides an audio file path and needs speech recognition, transcription, or ASR. Supports 52 languages and dialects, and common audio formats including WAV, MP3, FLAC, M4A, and OGG.
Qwen ASR Skill - Local Speech-to-Text
Transcribe audio files to text locally using the Qwen3-ASR-1.7B model.
Setup
Install dependencies into a Python 3.10+ virtual environment:
python -m venv .venv
source .venv/bin/activate
pip install qwen-asr soundfile silero-vad
For GPUs with compute capability < 7.0 (e.g. GTX 1060), install PyTorch 2.4.x with CUDA 11.8:
pip install torch==2.4.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu118
Usage
Run the transcription script with the path to an audio file:
python scripts/transcribe.py <audio_path>
Parameters
| Parameter | Description | Default |
|---|---|---|
audio_path |
Absolute path to audio file (required) | - |
--language |
Force language (e.g. Chinese, English). Auto-detect if omitted | Auto-detect |
--device |
Inference device: auto / cuda / cpu | auto |
--model-path |
Model path or HuggingFace ID | ~/models/Qwen3-ASR-1.7B |
--max-chunk-sec |
Max chunk duration for VAD splitting. Long audio is split at silence boundaries | 90 |
--max-new-tokens |
Max tokens to generate. Increase for long audio | 2048 |
Examples
Basic transcription:
python scripts/transcribe.py /path/to/audio.wav
Force language:
python scripts/transcribe.py /path/to/audio.mp3 --language Chinese
Force CPU inference:
python scripts/transcribe.py /path/to/audio.flac --device cpu
Output Format
The script outputs JSON to stdout and status info to stderr:
{"language": "Chinese", "text": "Transcribed text content"}
On error:
{"error": "Error description"}
Notes
- First run downloads the model (~4.7GB), cached for subsequent runs
- Auto mode: tries GPU (float16) first, falls back to CPU (float32) if VRAM is insufficient
- Supports: WAV, MP3, FLAC, M4A, OGG and other common audio formats
- 52 languages including Chinese, English, Japanese, Korean, French, German, etc.
- 22 Chinese dialects supported
- Long audio: Audio longer than 90s is automatically split at silence boundaries using silero-vad, transcribed chunk by chunk, then concatenated. This prevents OOM on limited VRAM GPUs.