Whisper-WebUI Premium - Ultra Fast and High Accuracy Speech to Text Transcripton App for All Languages - Windows, RunPod, Massed Compute 1-Click Installers - Supporting RTX 1000 to 5000 series
1-Click installers for Whisper-WebUI Premium. You can use this app to transcribe your Audio into literally 100 languages. This is currently state of the art open source speech to text app.
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Latest installer zip file : WhisperWeb_UI_v12.zip
This app has the combination of perfect implementation of the following repos and their advanced forks with so many additional new features and improvements (models auto downloaded, everything automatically installed into Python 3.11 venv, best quality presets fully ready):
Whisper from OpenAI : https://github.com/openai/whisper
NVIDIA NeMo Canary-Qwen-2.5B : https://huggingface.co/nvidia/canary-qwen-2.5b
Full tutorial video (2 May 2026) : https://www.youtube.com/watch?v=4lAk6sf1qF8
15 June 2026 - Version 12.3
Now when downloading model - when you first time use that model - it will show download progress on CMD
Now it will show selected and used model on CMD
Just run Windows_Install_Update.bat to update / install
8 June 2026 - Version 12.2
This is a major quality upgrade
Both Whisper and Canary models made more robust
Thus, if you were getting random errors on random files, it should not happen any more
Even though they were rare edge cases we fixed this issue
Whisper models seperated into below 2 model selection
Whisper (faster-whisper / CTranslate2)
Insanely Fast Whisper (Transformers)
Process based executing improved and cancel feature improved, now cancel immediately works properly
For Whisper models, the displayed messages during processing improved
Now you will see all messages on CMD and Gradio accurately
Default system presets updated to Fast Whisper Best Quality, Insane Fast Whisper Best Quality, Canary Qwen Best Quality
Now default selected preset / model is Fast Whisper Best Quality with Whisper Large-v3
Whisper Large-v3 model is the most capable robust model that excels at 100+ languages
I have done a very through research and experimentation to remake these presets with improved accuracy
Our accuracy is improved over 80% now
Now Word Timestamps is automatically selected along with new option Normalize Word Timestamp Output
This ensures that you get sentence level accurate subtitles / transcription not just 30 second long speeches
You can see newest quality research and new preset results tested on very hard to transcribe audio files as below
Word Error Rate (WER)
WER means Word Error Rate.
It measures word-level transcription mistakes:
WER = (substituted words + deleted words + inserted words) / reference words
So if the real subtitle has 100 words and the transcription has 6 total word mistakes, WER is 6%.
WER catches:
- missing words
- wrong words
- extra/repeated words
CER means Character Error Rate.
It is the same idea, but measured at the character level instead of word level:
CER = (substituted chars + deleted chars + inserted chars) / reference chars
CER catches smaller spelling/detail mistakes better.
Example:
Reference:
Wan 2.2 training
Prediction:
One 2.2 trainings
WER may be high because Wan became One and training became trainings.
CER may be lower because most letters are still similar.
For our use case, WER is the main metric because you care about missing words, wrong words, repeated words, and hallucinated extra words. CER is useful secondary evidence for spelling accuracy.
26 May 2026 - Version 12.0
With new zip file below errors fixed
Token: not provided Note: pyannote gated files require --token or HF_TOKEN on first download. [ERROR] Dependency source does not expose pytorch_model.bin: MonsterMMORPG/Wan_GGUF/pyannote_segmentation3
2 May 2026 - Version 11.1
Some installer bugs fixed
Enable Background Music Remover Filter - fixed
Enable Silero VAD Filter - fixed
30 April 2026 - Version 10.0
This is a quite big upgrade to our application
We now fully support NVIDIA NeMo Canary-Qwen-2.5B is an English speech recognition model : https://huggingface.co/nvidia/canary-qwen-2.5b
This model is currently State Of The Art (SOTA) Speech to Text model for English language
I have done extensive research and testing and it is set to best default parameters
Fully supporting all of the features our Whisper app were already supporting
Get the zip file, overwrite all previous files and run installer for update / upgrade
The model will be auto downloaded when you first time run
I also have compared with Whisper best configurations are here the comparison results - best results of Whisper taken
As you can see NVIDIA NeMo Canary-Qwen-2.5B is not only significantly better but also faster
15 April 2026 - Version 8.0
Diarization had some error and this is fixed
Mic tab completey remade and now both live transcription from microphone and offline transcription from microphone working
Live transcription quality is not that great
Both live transcription and offline transcription recordings from microphone will be saved in outputs folder
Live transcription will auto run but for offline transcription first record voice with microphone and then click Generate Subtitles button
Don't forget to select your working microphone and give permission for app to use your microphone from your browser
For update / install get the latest zip file, overwrite older files and run Windows_Install_Update.bat
4 April 2026 - Version 7.0
Now auto downloads Diarization files and thus you don't need to enter Hugging Face token and get permission
Now you can copy paste any YouTube link and generate subtitles
This was broken and now fixed
It will save generated files with same name as the video title
Now you can batch generate subtitles for YouTube video channels
Paste the video channel, enable batch and it will generate subtitles for every video
Set how many videos you want (scans latest ones)
You may get rate limited by YouTube
For update / install get the latest zip file, overwrite older files and run Windows_Install_Update.bat
8 April 2026 - Version 5.0
This is a massive update with so many new features
Get the latest zip file and make a fresh install please
1-Click to install on Windows, RunPod, SimplePod, Massed Compute, Linux
New preset save and load system with extremely well tested best_quality and fast pre-made presets
Presets are automatically loaded as you change them and also last used preset is remembered when you restart the app
Word Timestamps is enabled by default to improve quality but it also generates regular version as well automatically
Download transcription button
Open outputs folder button (all transcriptions automatically saved)
Load video / audio file directly from path (useful for platforms like RunPod where Gradio upload is slow)
The fast preset uses new custom in house implemented batch size 32 feature and it is literally blazing fast compared to all other existing Whisper apps and repos
Fully supporting all kind of video and audio formats upload with full preview
Batch folder processing process given folder all files automatically
Live transcription Window that shows latest transcription live while processing
At batch size 1 with best quality, 11x real time transcription speed (depends on GPU)
At batch size 32 fast preset up to 30x real time transcription speed (depends on GPU)
New feature Repeat Initial Prompt Every Window
Supports all Whisper models like Large V1, Large V3, Turbo, Distill Large, Tiny, etc
Supports following format outputs you can have checked all so all generated at the same time : SRT, WebVTT, txt, LRC,JSON, TSV
All outputs will have the same name as your input file name
With sub process working system, you can cancel any processing immediately with 0 RAM or VRAM leak
Fully supports Windows and Linux (use Massed Compute installer)
Based on Python 3.11 VENV and CUDA 13 and Torch 2.9.1 with pre-compiled libraries like Flash Attention
If you don't like output, try to enable / disable Condition On Previous Text it makes big difference
The app supports 100 languages and 32 models
Lots of Advanced Parameters and all set to best quality
Built in Background Music Remover Filter
Built in Voice Detection Filter
Supports Diarization
Fully detailed CMD output to watch entire progress
Extremely optimized VRAM usage as low as 6 GB GPUs
Some other utility features like YouTube, record from a Mic, T2T Translation, BGM Seperation
1 January 2026 Update V3.0
Installers upgraded to uv thus now installation on RunPod is like 100x faster and on Windows and Massed Compute like 10x faster
Enable Diarization was behind a gated repo, I cloned it into a public repo and now working perfect
Some other bugs also fixed
Get latest zip file, extract and overwrite older files, run Windows_Install_Update.bat to update or install
9 December 2025 Update V2.1
Installers are all upgraded, fixed and tested on RunPod and Massed Compute + Windows
Some bugs fixed in the app
Batch processing implemented
Now you can get multiple output formats at once
Get the latest zip file, extract and overwrite all and run Windows_Install_Update.bat for update
Windows Requirements
Python 3.11, FFmpeg, CUDA 13, cuDNN, C++ tools and Git
If it doesn't work make sure to below tutorial and install everything exactly as shown in this below tutorial
Massed Compute (Recommend Cloud) :
Please register via this link : https://vm.massedcompute.com/signup?linkId=lp_034338&sourceId=secourses&tenantId=massed-compute
Use our coupon SECourses
Our coupon works on all GPUs now
H100 has amazing price and speed but you can use like RTX A6000 ADA as well
Full details here : https://www.patreon.com/posts/26671823
Then select our image SECourses from Creator dropdown
Then follow Massed_Compute_Instructions_READ.txt
Same as my any other Massed Compute installer script
Example tutorial for learn how to install and use Massed Compute
(Starts at 12:58) : https://youtu.be/KW-MHmoNcqo?si=G1WbG-Qw4ujWvOtG&t=778
RunPod (Cloud):
Please register via this link : https://runpod.io?ref=1aka98lq
Then follow Runpod_Instructions_READ.txt
Same as my any other RunPod installer script
Use the template written in Runpod_Instructions_READ.txt file
Example tutorial for learn how to install and use RunPod
(starts at 22:03) : https://youtu.be/KW-MHmoNcqo?si=QN8X8Sjn13ZYu-EU&t=1323