Left gets fewer words wrong. Lower has the final text ready sooner.
Reson8 is ahead of Google Chirp 3 on both datasets together, time to first text and final-text delay. The Pipecat Dataset and The Ocular Dataset are too close to call.
Last updated Methodology by Dileep Chagam
Lower is better on every measure. Too close to call means the likely ranges overlap. For the wider field, see our pick of the best voice AI APIs for real-time audio.
Reson8 is more accurate on the public clips. On the 1,000 public Pipecat clips, Google Chirp 3 scores 2.76% and Reson8 2.38%, so Reson8 makes fewer errors by 0.37 points. On the eight licensed Ocular recordings, Google Chirp 3 scores 2.00% and Reson8 2.10%, with likely ranges of 1.77 to 2.25% and 1.86 to 2.35%. The ranges overlap, so the difference is too close to call. Word error rate counts incorrect, missing, and extra words, so lower is better.
Reson8 is more accurate on the public clips. On the 1,000 public Pipecat clips, Google Chirp 3 scores 2.76% and Reson8 2.38%, so Reson8 makes fewer errors by 0.37 points. On the eight licensed Ocular recordings, Google Chirp 3 scores 2.00% and Reson8 2.10%, with likely ranges of 1.77 to 2.25% and 1.86 to 2.35%. The ranges overlap, so the difference is too close to call. Word error rate counts incorrect, missing, and extra words, so lower is better.
No. Reson8 finishes the transcript 2.08s sooner. Google Chirp 3 has the final transcript 4.48s after the speaker stops and Reson8 2.40s, at the median. Both are measured on the same 206 streamed turns.
Reson8 finishes the transcript 2.08s sooner, and the two are too close to call on real conversations. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.
Yes, both return partial text before the speaker stops. Google Chirp 3 shows first text after 4.19% and Reson8 after 2.93%, at the median.
Cekura runs these simulated calls on your agent and scores every one.