[1/4] How well do speech recognition systems handle real conversations in 21 languages?
Today we're releasing DAI-ASR-I18N, a benchmark that evaluates 14 systems on speech recognition and speaker diarization in natural, unscripted conversation
Oct 1, 2026 · 2:48 AM UTC
[2/4] What we found - part 1
1. English scores hide big gaps between systems in other languages
2. Microsoft AI’s MAI-Transcribe-2 leads ASR in 18 of 21 languages; ElevenLabs' Scribe v2 leads in the other three
[3/4] What we found - part 2
3. Every dedicated diarization model beat every combined transcription-and-diarization system; NVIDIA Nemotron 3 Diarization leads in 19 of 21 languages
4. Every system struggles most with overlapping speech
[4/4] We're releasing the dataset and our inference and evaluation harness publicly.
Results: research.withdavid.ai/blog/a…
Data: huggingface.co/datasets/davi…
Evals or research collaboration:
[email protected]
[email protected]
A 21-language benchmark on unscripted conversation is the right test, since most published WER comes from read speech. For anyone choosing a system: read the diarization error separately from the word error. They diverge hard on crosstalk. brss.fyi/1ux8






