HeyMeco
Joined 1 year ago
Joined 1 year ago
The developer preview is intended for RTX Spark
This tool is a result of me realising there are no real options for interview transcriptions with speaker detection that can be used in an university study evaluation context where you do not upload the data into a someone’s else’s cloud with questionable privacy policies.
Feature summary:
- Diarized transcription — identifies speakers and assigns words to each speaker
- Plain-text output with timestamps and speaker labels
- Interactive HTML with: Color-coded speaker segments Word-level highlighting synced to playback - Click any word or segment to seek in the audio
- Rename speakers
- Built-in audio player (with playback speed selection)
"Was it faster than doing it solo? Probably yes, on the order of 3–5× for the work captured in these transcripts, with the speedup concentrated in:
Mass refactor / rename work (10× or more — Claude can rename a function and update 200 call sites in minutes). Code review breadth (subagent fan-out reads more files per hour than any human can). Performance analysis writeups (the “table of metrics + paragraph of prose” format is something Claude is genuinely good at and is tedious for humans)."
And it has one trick up its sleeve:
▶ If you turn it off and on 12x times it switches to a zigbee mode so I was able to integrate it into my existing HomeAssistant setup even easier