We just rolled out a major update to [ComfyUI-QwenASR](https://github.com/1038lab/ComfyUI-QwenASR) (v1.1.0). The goal of this release was simple: eliminate the friction between raw audio recognition and usable text/subtitle output in ComfyUI workflows.

Here is a breakdown of what changed:

**1. Migration to Transformers 5 & Official Native Models**

We have completely deprecated the legacy checkpoints and rewritten the backend to use official Hugging Face native models (Qwen3-ASR-1.7B-hf, Qwen3-ASR-0.6B-hf, and Qwen3-ForcedAligner-0.6B-hf) powered by transformers >= 5.13.0.

Zero fragile custom backends: Pure upstream PyTorch execution.

Lower VRAM & faster generation: Noticeable performance gains on both NVIDIA GPUs and Apple Silicon Macs.  


**2. Production-Ready Text Normalization (ITN)**

Raw ASR output usually outputs verbatim acoustic phrasing, which looks messy. Version 1.1.0 integrates automatic Inverse Text Normalization:

Spoken numbers, percentages, and decimals are automatically converted into proper numerals (e.g., spoken numbers become standard digits).

Phonetically spaced acronyms (like "A S R" or "U S B") are merged into clean abbreviations.

Cultural idioms and phrases are protected through built-in whitelists so words are not erroneously replaced.  


**3. Hot-Reloadable Multi-Language Custom Dictionary**

All normalization and correction rules now reside in an external itn\_rules.json file. You can add custom acronyms, brand names (e.g., DeepSeek, ComfyUI, ChatGPT), and terminology across English, Chinese, Japanese, Korean, or French. Changes take effect on your very next run with no ComfyUI restart required.



**4. A Specialized Three-Node Toolkit**

ASR (QwenASR): Fast, lightweight speech-to-text transcription for voice prompting.

Subtitle (QwenASR): Chunks speech into natural sentences based on punctuation, pauses, or line length, with one-click .srt file export.

Forced Align (QwenASR): Built specifically for long continuous audio (podcasts, lectures). It uses an iterative speaking-rate windowing approach to prevent edge drift and duration limits. Leaving the transcript text empty automatically transcribes and aligns in a single pass.

Full installation steps and ready-to-use sample workflows can be found in the README on our GitHub: [https://github.com/1038lab/ComfyUI-QwenASR](https://github.com/1038lab/ComfyUI-QwenASR)



Looking forward to your thoughts and hearing how it fits into your ComfyUI audio and video pipelines!

[Update] ComfyUI-QwenASR v1.1.0: Full Transformers 5 & Official Native Models Upgrade, Smart ITN, and Long-Form Forced Alignment