Small addition / changes
What's Changed
- [New] add option to not use .en model for english language
- [Fix] fix cases where translation will show error when it's only translating digits of number
Full Changelog: 1.3.9...1.3.10
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 Translateas module. - If you previously installed
speech translateas a module, you can update by doingpip 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
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 UIfont 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