Speech Recognition

Studio benchmarks hide the noise and crosstalk that cuts accuracy in half for real meetings.

Streaming works live, batch works accurate—pick the wrong one and your transcription fails.

Word Error Rate alone misses what matters most in real meeting transcriptions.

Poor audio conditions, not weak AI models, cause meeting transcription failures.

Different architectures handle meeting audio's challenges in drastically different ways.

Most vendors advertise accuracy their benchmarks never actually test in real multilingual meetings.

AI struggles with technical terms even as general meeting transcription accuracy soars.

Speech recognition systems fail twice as often on Black speakers and non-native accents.

Current systems drop overlapping speech or misassign it, but real meetings are nearly half overlap.