1.3.8.1 - Fix model checking

This release fix model checking bug in the previous version

What's Changed

• Fix faster whisper model checking #63

Full Changelog: 1.3.8...1.3.8.1

Notes

• Before downloading / installing please take a look at the wiki and read the getting started section.
• Use the CUDA version for GPU support
• Linux/Mac user can follow this installation note to install Speech Translate as module.
• 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 --no-deps
• 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 Installation:

OS	Installation from Prebuilt binary	Installation as a Module	Installation from Git
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 (Alternatively, you can make a loopback to capture your system audio as virtual input (like mic input) by using this guide/tool: [Voicemeeter on Windows]/[YT Tutorial] - [pavucontrol on Ubuntu with PulseAudio] - [blackhole on MacOS]
• Internet connection is needed only for translation with API & downloading models (If you want to go fully offline, you can setup LibreTranslate on your local machine and set it up in the app settings)
• Recommended to have Segoe UI font installed on your system for best UI experience (For OS other than windows, you can see this: Ubuntu - MacOS)
• Recommended to have capable GPU with CUDA compatibility (prebuilt version is using CUDA 11.8) for faster result. Each whisper model has different requirements, for more information you can check it directly at the whisper repository.

Size	Parameters	Required VRAM	Relative speed
tiny	39 M	~1 GB	~32x
base	74 M	~1 GB	~16x
small	244 M	~2 GB	~6x
medium	769 M	~5 GB	~2x
large	1550 M	~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 model speed will be significantly faster and have smaller vram usage, for more information about this please visit faster-whisper repository