SpotifyTranscripts
rapviz
SpotifyTranscripts | rapviz | |
---|---|---|
1 | 1 | |
140 | 6 | |
- | - | |
6.3 | 6.9 | |
5 months ago | 7 days ago | |
JavaScript | TypeScript | |
- | MIT License |
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SpotifyTranscripts
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Show HN: PodText.ai – Search anything said on a podcast, Highlight text to play
This is great, I was working on something similar in the last few days, but since it is hard to cover every podcast, I stopped to think of a way to niche down. I feel your pain with GPU and scalability to transcript podcasts.
I was thinking of adding something like this for the UI https://github.com/johan-akerman/SpotifyTranscripts in case you find it useful.
Good luck! It is a really nice project.
rapviz
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How do I "run" a program from Github on my Windows PC?
Sorry for being a complete novice to this, although I've used Github in the past, I'm not entirely sure how to download and run this application on my PC: https://github.com/michaelfromyeg/RapViz
What are some alternatives?
Saveddit - Search and Filter through your Saved Reddit Posts
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autocropper.io - API to automatically crop and output individual photos from multi-photo scans (deprecated)
rowy - Low-code backend platform. Manage database on spreadsheet-like UI and build cloud functions workflows in JS/TS, all in your browser.
threaddit - Threaddit is a full-stack Reddit clone; it's a comprehensive web application inspired by Reddit, built using Flask and its diverse libraries for the backend, combined with PostgreSQL for robust database management. The frontend is developed using React.js and its rich set of libraries, offering a seamless and dynamic user experience.
superset - Apache Superset is a Data Visualization and Data Exploration Platform
realtime-transcription-playground - A real-time transcription project using React and socketio
codebase - a software and writing repository
modal-examples - Examples of programs built using Modal
dtale - Visualizer for pandas data structures
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
pyannote-audio - Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding