Left gets fewer words wrong. Lower has the final text ready sooner.
Reson8 is ahead on both datasets together and the Pipecat Dataset, and Smallest Pulse on time to first text and final-text delay. The Ocular Dataset is 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. Our guide explains how word error rate is measured.
Reson8 is more accurate on both datasets. On the 1,000 public Pipecat clips, Reson8 scores 2.38% and Smallest Pulse 3.59%, so Reson8 makes fewer errors by 1.20 points. On the eight licensed Ocular recordings, Reson8 scores 2.10% and Smallest Pulse 3.66%, so Reson8 makes fewer errors by 1.56 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Reson8 is more accurate on both datasets. On the 1,000 public Pipecat clips, Reson8 scores 2.38% and Smallest Pulse 3.59%, so Reson8 makes fewer errors by 1.20 points. On the eight licensed Ocular recordings, Reson8 scores 2.10% and Smallest Pulse 3.66%, so Reson8 makes fewer errors by 1.56 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
No. Smallest Pulse finishes the transcript 1.34s sooner. Reson8 has the final transcript 2.40s after the speaker stops and Smallest Pulse 1.06s, at the median. Both are measured on the same 206 streamed turns.
It is a trade-off. Reson8 makes fewer errors on real conversations, while Smallest Pulse finishes the transcript 1.34s sooner. 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. Reson8 shows first text after 2.93% and Smallest Pulse after 3.46%, at the median.
Cekura runs these simulated calls on your agent and scores every one.