Meeting transcription bottleneck shifts to speaker attribution, not accuracy
Mysterious_Sign_9501 · reddit · 2026-08-26
After testing various AI transcription tools, the author notes that word-level accuracy is now solid (upper 90s%). The real bottleneck is speaker diarization—figuring out who said what—especially in multi-person calls with crosstalk. A transcript with wrong attribution is arguably more useless than one with lower accuracy. Tools like Otter and Vomo.ai were tested, with Vomo performing better on 3+ calls, though overlapping speech remains a challenge.
More from Apps
- Rotating providers for credits, Grok offers faster model switching — curious_vii · 2026-08-26
- Synthesia Launches Interactive Avatars; AI Press Officer Built with Claude & LiveKit — alexvoica · 2026-08-26
- Synthesia Introduces AI Press Officer: Interactive Avatar for Company Inquiries — alexvoica · 2026-08-26
- ChatGPT Desktop App Shows Wrong Model Name '5.6 Sol' — JoseMSB · 2026-08-26
- User reports LaTeX rendering issues in ChatGPT on Android — Trollphile · 2026-08-26
- Google AI Search usage higher than perceived; dev habits — threepointone · 2026-08-26