Left gets fewer words wrong. Lower has the final text ready sooner.
Inworld STT-1 is ahead on final-text delay, and Smallest Pulse on both datasets together. The two tie on time to first text. 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. Our guide explains how word error rate is measured.
Smallest Pulse is more accurate on the public clips. On the 1,000 public Pipecat clips, Inworld STT-1 scores 5.44% and Smallest Pulse 3.59%, so Smallest Pulse makes fewer errors by 1.85 points. On the eight licensed Ocular recordings, Inworld STT-1 scores 2.72% and Smallest Pulse 3.66%, with likely ranges of 1.67 to 4.68% and 3.34 to 3.99%. The ranges overlap, so the difference is too close to call. Word error rate counts incorrect, missing, and extra words, so lower is better.
Smallest Pulse is more accurate on the public clips. On the 1,000 public Pipecat clips, Inworld STT-1 scores 5.44% and Smallest Pulse 3.59%, so Smallest Pulse makes fewer errors by 1.85 points. On the eight licensed Ocular recordings, Inworld STT-1 scores 2.72% and Smallest Pulse 3.66%, with likely ranges of 1.67 to 4.68% and 3.34 to 3.99%. The ranges overlap, so the difference is too close to call. Word error rate counts incorrect, missing, and extra words, so lower is better.
They finish the transcript at the same median time. Inworld STT-1 has the final transcript 1.06s after the speaker stops and Smallest Pulse 1.06s, at the median. Both are measured on the same 206 streamed turns.
Inworld STT-1 and Smallest Pulse are level on the two figures a voice agent depends on most. 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. Inworld STT-1 shows first text after 10.60% and Smallest Pulse after 3.46%, at the median.
Cekura runs these simulated calls on your agent and scores every one.