> My main motivation to build this is that I read faster than I listen
Yes! However occasionally I find it useful to refer to the original video (especially when I want to share a video at a certain timestamp.) Searchable transcripts are a great way to navigate a video if they have links that jump to the relevant timestamp in the video.
So I designed a special file format and web app based on oTranscribe + Markdown:
I made a tool to convert YouTube SBV/TTML files; it should be possible to add support for one of your output formats: https://github.com/Leftium/otrgen
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There was a similar show HN[1] that opened my eyes to OpenAI Whisper, however your python script provides a better starting point than a bash script. I'll probably reference both projects when I make my own projects (including a beat-aware YouTube player that needs the audio data for beat-detection analysis.)
Yes, you're right, that's a good idea! I just checked the oTranscribe Netlify app and I think it's pretty cool.
However, I agree that it could be improved by having cleaner (transcribed) text. You should be able to integrate my approach pretty easily since srt and vtt output formats maintain the time stamps.
Let me know if there's something I can do to make your life easier. Otherwise, naturally, feel free to fork my repo etc. :-)
> My main motivation to build this is that I read faster than I listen
Yes! However occasionally I find it useful to refer to the original video (especially when I want to share a video at a certain timestamp.) Searchable transcripts are a great way to navigate a video if they have links that jump to the relevant timestamp in the video.
So I designed a special file format and web app based on oTranscribe + Markdown:
- https://raw.githubusercontent.com/Leftium/oTranscribe/refs/h...
- https://otranscribe.netlify.app/?vsl=definedefine
I made a tool to convert YouTube SBV/TTML files; it should be possible to add support for one of your output formats: https://github.com/Leftium/otrgen
---
There was a similar show HN[1] that opened my eyes to OpenAI Whisper, however your python script provides a better starting point than a bash script. I'll probably reference both projects when I make my own projects (including a beat-aware YouTube player that needs the audio data for beat-detection analysis.)
[1]: https://hw.leftium.com/#/item/41473379
Yes, you're right, that's a good idea! I just checked the oTranscribe Netlify app and I think it's pretty cool.
However, I agree that it could be improved by having cleaner (transcribed) text. You should be able to integrate my approach pretty easily since srt and vtt output formats maintain the time stamps.
Let me know if there's something I can do to make your life easier. Otherwise, naturally, feel free to fork my repo etc. :-)