Search for a command to run...
Articles tagged with #artificial-intelligence
AI speaker diarization accuracy claims look good in benchmarks. In production on real-world audio, the failure modes are specific, predictable, and largely unaddressed by the tools you are using.
Human QA and AI QA catch completely different error types. Understanding which errors each method finds — and misses — is the only way to build a QA process that actually works.
AI transcription accuracy has never been better. AI transcript QA failure rates have never been higher. The reason is not accuracy — it is everything that happens after the transcript is delivered.
Whisper Large-v3 benchmarks on clean audio look great. Here is what actually happens on background noise, heavy accents, cross-talk, and technical vocabulary.
