QWEN3-Asr-Toolkit: Open Open Tool of Python Command-line

Kwarts has released QWEN3-Asr-TowkitPython CLI with a MIT LICENCE RESTING THE QWEN3-ARR-BLA-BLA-FLASH API 3-minute / 10 MB for each request Limit Vad-Anazi Chunking, Corresponding API Calls, and automatic re-automatically / format format with FFMPEG. The result is strong, the pipes of a strong hour in accordance, the injection injection, and the performance of the pure text. Python ≥3.8 What you need, enter with:

pip install qwen3-asr-toolkit

That is only the best of API

• A long audio management. Toolkit Slices Inction Uses Donations of a Voice Work (VAD) For natural habits, keeping each chunk below API / size of API size, and combine the results in a row.
• Corresponding matches. The lake of the string moves many chunks at one time to Dashscope Endpoints, improving the 1 cjock latency by the hour. He regulates a consistency of Naturn -j/--num-threads.
• Format and standard measuring. Any normal Audio / Video A bowl (MP4 / Mov / MKV / MK3 / WAV / M4A, etc.) You are converted to the required API Mono 16 Khz before moving. Requires ffpegeg placed on the road.
• Cleaning text and context. The tool includes processing after reducing multiplication / halucinations and support vaccination BIAS recognition for domain conditions; API is not less and shown Language detection including The Normal Text (ITN) Toggles.

Prince QWEN3-Asr-Flash API repairs and exformes ≤3 min length of time and ≤10 MB To be loaded with each call. That is reasonable for applicable applications but are very bad in long media. Toolkit works very well – the separation of Vad-Anazi + the same calls – incoming groups can bind large historical histories or dumps live without writing orchestaration from the beginning.

Quick start

1. Add Requirements

# System: FFmpeg must be available
# macOS
brew install ffmpeg
# Ubuntu/Debian
sudo apt update && sudo apt install -y ffmpeg

2. Add CLI

pip install qwen3-asr-toolkit

3. Prepare Warnings

# International endpoint key
export DASHSCOPE_API_KEY="sk-..."

4. Run

# Basic: local video, default 4 threads
qwen3-asr -i "/path/to/lecture.mp4"

# Faster: raise parallelism and pass key explicitly (optional if env var set)
qwen3-asr -i "/path/to/podcast.wav" -j 8 -key "sk-..."

# Improve domain accuracy with context
qwen3-asr -i "/path/to/earnings_call.m4a" 
  -c "tickers, CFO name, product names, Q3 revenue guidance"

The issues you will use:
-i/--input-file (File method or http / https URL), -j/--num-threads, -c/--context, -key/--dashscope-api-key, -t/--tmp-dir, -s/--silence. The output printed and stored as .txt.

Construction of small pipes

1. Abduct Location file or URL → 2) Surround Finding Borders of Peace → 3) Chunk Under the API CAPS → 4) Repeat to 16 khz mono → 5) Move to move In dashscope → 6) -The straight alongside Parts in a row → 7) Postal process Text (Detup, Repeat) → 8) Send .txt the text.

Summary

QWen3-Asr-Toolkit turns QWen3-Asr-Flash into a long-sound qwen. Production, Phoures The Package version, Verify the ENDPOINDS / District keys, and list the tune rope to your network and QPS – pip install qwen3-asr-toolkit and the ship.

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