1.3.6 - Bug Fixes and Enhancement

It seems that we have reached 7.4k download and almost 300 stars as of the time i release this 🚀

Thank you very much everyone for the participation in downloading, starring, forking, opening discussion, and submitting bug reports or feature request.

What's Changed

• Fixed translate with whisper not showing result in record
• Fixed continue after model download prompt
• Fixed random crashing when using faster whisper
• Fixed getting frame window in record
• Fixed log format when clear or change mode
• Changed some default option
• FFmpeg is now bundled with the app using static-ffmpeg #56 thanks to @zackees for the suggestion
• Added ways to filter result to counter hallucination
• Added optional silero vad that can be used alongside webrtcvad if possible on record
• Added setting for record min input length

Full Changelog: 1.3.5...1.3.6

Notes

• Before downloading / installing please take a look at the wiki and read the getting started section.
• If you previously installed speech translate as a module, you can update by doing pip install -U git+https://github.com/Dadangdut33/Speech-Translate.git --upgrade --force-reinstall
• If you install from installer, you can download and launch the installer below to update
• If you have any suggestions or found any bugs please feel free to open a disccussion or open an issue

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Requirements

• Compatible OS:

OS	Prebuilt binary	As a module
Windows	✔️	✔️
MacOS	❌	✔️
Linux	❌	✔️

* Python 3.8 or later (3.11 is recommended) for installation as module.

• Speaker input only work on windows 8 and above.
• Internet connection (for translation with API)
• Recommended to have capable GPU with CUDA compatibility (prebuilt version is using CUDA 11.8) to run each model. Each whisper model has different requirements, for more information you can check it directly at the whisper repository.

Size	Parameters	English-only model	Multilingual model	Required VRAM	Relative speed
tiny	39 M	tiny.en	tiny	~1 GB	~32x
base	74 M	base.en	base	~1 GB	~16x
small	244 M	small.en	small	~2 GB	~6x
medium	769 M	medium.en	medium	~5 GB	~2x
large	1550 M	N/A	large	~10 GB	1x

* This information is also available in the app (hover over the model selection in the app and there will be a tooltip about the model info). Also note that when using faster-whisper, the speed will be significantly faster and the required vram size will be reduced depending on the usage, for more information about this please visit faster-whisper repository