| title | Abraji 2024: Turning Audio and Video into useable data | ||||||||||
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Jonathan Soma, Knight Chair in Data Journalism, Columbia Graduate School of Journalism
- Contact: jonathan.soma@gmail.com, @dangerscarf
- A few links: Practical AI for Investigative Journalism, jonathansoma.com, Everything I Know
Slides are here, and my site from yesterday's Abraji session about analyzing documents can be found here
- MacWhisper for macOS
- EasyWhisper for Windows and macOs
- WhisperJAX to try it out online
- Facebook's MMS to try out a non-Whisper model
- insanely fast whisper for Python (see "Audio transcription" notebook below)
- yt-dlp for download videos (YouTube, TikTok, etc) from Python or the command line
- statcher for downloading videos without code
- ffmpeg for manipulating videos in a far too technical way
- Shutterencoder or ffworks for a less technical interface to ffmpeg
We have one example of using Claude for Sheets to analyze text. You will need to install Claude for Sheets first.
We have three examples of using Python code to analyze audio and video: