Left gets fewer words wrong. Lower has the final text ready sooner.
Google Chirp 2 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. Google Chirp 2 has a newer release: Google Chirp 3 vs Smallest Pulse.
Last updated Methodology by Dileep Chagam
Lower is better on every measure. Too close to call means the likely ranges overlap.
Google Chirp 2 is more accurate on both datasets. On the 1,000 public Pipecat clips, Google Chirp 2 scores 3.01% and Smallest Pulse 3.59%, so Google Chirp 2 makes fewer errors by 0.58 points. On the eight licensed Ocular recordings, Google Chirp 2 scores 2.59% and Smallest Pulse 3.66%, so Google Chirp 2 makes fewer errors by 1.06 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Google Chirp 2 is more accurate on both datasets. On the 1,000 public Pipecat clips, Google Chirp 2 scores 3.01% and Smallest Pulse 3.59%, so Google Chirp 2 makes fewer errors by 0.58 points. On the eight licensed Ocular recordings, Google Chirp 2 scores 2.59% and Smallest Pulse 3.66%, so Google Chirp 2 makes fewer errors by 1.06 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
No. Smallest Pulse finishes the transcript 3.44s sooner. Google Chirp 2 has the final transcript 4.50s 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. Google Chirp 2 makes fewer errors on real conversations, while Smallest Pulse finishes the transcript 3.44s 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. Google Chirp 2 shows first text after 3.80% and Smallest Pulse after 3.46%, at the median.
Cekura runs these simulated calls on your agent and scores every one.