Highlighter is a project designed to automatically extract real-time highlights from YouTube livestreams. Highlight timestamps are initially detected based on chat traffic surges, and these timestamps are then refined using context from video transcripts generated by Speech-to-Text (STT). This approach combines both audience reactions and content analysis for more accurate and meaningful highlight extraction.
After extracting the highlights, Highlighter can automatically upload them back to YouTube for immediate sharing.
- Real-Time Highlight Detection: Automatically identifies potential highlight moments during YouTube livestreams by analyzing chat traffic spikes.
- Contextual Highlight Refinement: After detecting an initial highlight based on chat activity,
Highlighteruses STT to generate transcripts from the video, refining the timestamp range of the highlight based on the content's context. - Seamless Automation: The process of detecting, refining, and saving highlights is fully automated, requiring no manual intervention.
- Highlight Saving: Extracted highlights are stored on cloud storage for further review, editing, or sharing.
- Automatic YouTube Upload: Once highlights are extracted, videos are automatically uploaded to your YouTube account, making the highlights available for viewers almost instantly.
For more detailed documentation, including advanced usage, configuration examples, and troubleshooting tips, please refer to the GitHub Wiki for this project.