Watch a foreign language livestream with live translated subtitles
Follow a lecture in a foreign language using microphone mode
Keep captions on screen while watching an AI interview in another language
Study a language by comparing bilingual subtitles in real time
| nbzz/whicc | repoprompt/repoprompt-classic | zaidmukaddam/swift-ai-sdk | |
|---|---|---|---|
| Stars | 35 | 35 | 35 |
| Language | Swift | Swift | Swift |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 3/5 | 3/5 |
| Audience | general | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires installing and configuring a separate LM Studio translation server, without it, subtitles are not translated.
Whicc is a macOS app that shows real time translated subtitles over any video you are watching, whether that is a livestream, a recorded video, or even sound picked up from your microphone during a lecture. The idea is not to be a perfect translator, but to always be there so you can follow along in a language you do not fully understand. The app works by running speech recognition locally on your Mac using Apple Silicon, so the audio itself never leaves your machine. It uses one recognition model tuned for Chinese and another tuned for other languages. Once the speech is turned into text, that text is sent to a separate translation model that you set up yourself using a free program called LM Studio, which can run on the same Mac or on another computer on your home network. Whicc does not include or ship a translation model itself. Without a translation service configured, the app still shows live recognized text, but it will not produce a finished translated caption. Subtitles appear in a small floating window that stays on top of other apps and can be repositioned. The app also builds a private glossary of terms over time, learning from the content you watch so translations of specific vocabulary improve in later sessions. Requirements are macOS 15 or newer running on Apple Silicon, an internet connection for the first download of the speech models, and a separate machine or the same Mac to run the translation service. Normal users can download a ready made app from the releases page, while developers can build it from source following the project's development guide. The project is released under the MIT license.
A macOS app that overlays real time translated subtitles on any video or livestream using local speech recognition and a translation model you set up yourself.
Mainly Swift. The stack also includes Swift, Python, SwiftUI.
MIT license lets you use, copy, modify, and sell the app freely as long as you keep the original copyright notice.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly general.
This repo across BitVibe Labs
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