How I Built a Tool That Transcribes TikTok Live Videos Using Whisper API
Recently, I built a small project using OpenAI’s Whisper API to transcribe TikTok live videos in real-time. In this article, I’ll show you what I did, how I did it, and highlight a few features.
The Script is deployed as a Docker container and can be accessed here (no SSL atm): http://134.122.78.219/ (plese hit me up with feedback).
What the TikTokTranscript0r Does
The TikTokTranscript0r takes TikTok live video URLs and turns their audio into text transcripts in real-time. It uses:
- Gradio for a simple, clean interface
- yt-dlp to grab audio from TikTok streams
- FFmpeg to handle audio recording and processing
- OpenAI’s Whisper API for accurate speech-to-text transcription
How It Works (in Simple Steps)
Enter a TikTok live URL and your OpenAI API key. The tool records live audio segments using FFmpeg, ensuring continuous transcription without gaps. Whisper API (OpenAI) converts these audio segments into accurate text. The transcribed text updates live as the chunks come back, with options to download the full transcript and audio recording afterward.
Key Features That Make It Stand Out
Audio Optimization:
I used advanced audio processing (noise reduction, frequency normalization) for clearer speech recognition, leading to better transcripts.
Segment Overlapping:
Each audio segment overlaps slightly with the previous one. This prevents missing words between segments and improves transcription flow.
Duplication Detection:
The TikTokTranscript0r automatically detects and removes duplicate or repeating phrases using the Levenshtein distance algorithm, significantly improving readability.
Persistent Downloads:
Even after stopping the tool, audio and transcripts remain downloadable.
Use Cases
- Content creators who want immediate transcripts of their TikTok Lives
- Marketers or analysts monitoring live events
- Accessibility applications for the hearing impaired
Next Steps
I’m still refining the tool. Future plans include:
- Adding real-time summaries
- Expanding support for other live streaming platforms
- Possibly integrating translation features directly into the workflow
- Making it more accessable through Docker
- SSL of course
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