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https://github.com/Purfview/whisper-standalone-win
Whisper & Faster-Whisper standalone executables for those who don't want to bother with Python.
https://github.com/Purfview/whisper-standalone-win
asr ctranslate2 faster-whisper faster-whisper-xxl openai speech-recognition speech-to-text subtitles transcriber uvr whisper whisper-faster whisper-faster-xxl whisperx
Last synced: 8 days ago
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Whisper & Faster-Whisper standalone executables for those who don't want to bother with Python.
- Host: GitHub
- URL: https://github.com/Purfview/whisper-standalone-win
- Owner: Purfview
- Created: 2023-02-25T18:32:55.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-11T15:31:05.000Z (7 months ago)
- Last Synced: 2024-04-11T17:38:53.789Z (7 months ago)
- Topics: asr, ctranslate2, faster-whisper, faster-whisper-xxl, openai, speech-recognition, speech-to-text, subtitles, transcriber, uvr, whisper, whisper-faster, whisper-faster-xxl, whisperx
- Homepage:
- Size: 142 KB
- Stars: 727
- Watchers: 25
- Forks: 39
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: changelog.txt
Awesome Lists containing this project
- awesome-whisper - whisper-standalone-win - Standalone Windows executable for Whisper and Faster Whisper. (CLI tools / Self-hosted)
README
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[Standalone executables](https://github.com/Purfview/whisper-standalone-win/releases) of [OpenAI's Whisper](https://github.com/openai/whisper) & [Faster-Whisper](https://github.com/guillaumekln/faster-whisper) for those who don't want to bother with Python.
**Faster-Whisper** executables are x86-64 compatible with Windows 7, Linux v5.4, macOS v10.15 and above.
**Faster-Whisper-XXL** executables are x86-64 compatible with Windows 7, Linux v5.4 and above.
**Whisper** executables are x86-64 compatible with Windows 7 and above.
Meant to be used in command-line interface or in programs like [Subtitle Edit](https://github.com/SubtitleEdit/subtitleedit), [Tero Subtitler](https://github.com/URUWorks/TeroSubtitler), [FFAStrans](https://ffastrans.com/wp/), [AviUtl](https://github.com/oov/aviutl_subtitler).
Faster-Whisper is much faster & better than OpenAI's Whisper, and it requires less RAM/VRAM.
## Usage examples:
* `whisper-faster.exe "D:\videofile.mkv" --language English --model medium --output_dir source`
* `whisper-faster.exe "D:\videofile.mkv" -l English -m medium -o source --sentence`
* `whisper-faster.exe "D:\videofile.mkv" -l Japanese -m medium --task translate --standard`
* `whisper-faster.exe --help`
## Notes:
Executables & libs can be downloaded from `Releases`. [at the right side of this page]
Don't copy programs to the Windows' folders! [run as Administrator if you did]
Programs automatically will choose to work on GPU if CUDA is detected.
For decent transcription use not smaller than `medium` model.
Guide how to run the command line programs: https://www.youtube.com/watch?v=A3nwRCV-bTU
Examples how to do batch processing on the multiple files: https://github.com/Purfview/whisper-standalone-win/discussions/29
## Standalone Whisper info:
Vanilla Whisper, compiled as is - no changes to the original code.
A reference implementation, stagnant development, atm maybe useful for some tests.
## Standalone Faster-Whisper info:
Some defaults are tweaked for movies transcriptions and to make it portable.
Features various new experimental settings and tweaks.
Shows the progress bar in the title bar of command-line interface. [or it can be printed with `-pp`]
By default it looks for models in the same folder, in path like this -> `_models\faster-whisper-medium`.
Models are downloaded automatically or can be downloaded manually from: https://huggingface.co/Systran
`beam_size=1`: can speed-up transcription twice. [ in my tests it had insignificant impact on accuracy ]
`compute_type`: test different types to find fastest for your hardware. [`--verbose=true` to see all supported types]
To reduce memory usage try incrementally: `--best_of=1`, `--beam_size=1`, `-fallback=None`.
## Standalone Faster-Whisper-XXL info:
Includes all Standalone Faster-Whisper features +the additional ones, for example:
Preprocess audio with MDX23 Kim_vocal_v2 vocal extraction model.
Alternative VAD methods: 'silero_v3', 'silero_v4', 'pyannote_v3', 'pyannote_onnx_v3', 'auditok', 'webrtc'.
Read more about it in [the Discussions' thread](https://github.com/Purfview/whisper-standalone-win/discussions/231).
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