Left gets fewer words wrong. Lower has the final text ready sooner.
Google Chirp 2 is ahead of GPT-4o Transcribe on both datasets together, the Pipecat Dataset, the Ocular Dataset and final-text delay. Google Chirp 2 has a newer release: Google Chirp 3 vs GPT-4o Transcribe.
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 GPT-4o Transcribe 6.85%, so Google Chirp 2 makes fewer errors by 3.84 points. On the eight licensed Ocular recordings, Google Chirp 2 scores 2.59% and GPT-4o Transcribe 3.90%, so Google Chirp 2 makes fewer errors by 1.31 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 GPT-4o Transcribe 6.85%, so Google Chirp 2 makes fewer errors by 3.84 points. On the eight licensed Ocular recordings, Google Chirp 2 scores 2.59% and GPT-4o Transcribe 3.90%, so Google Chirp 2 makes fewer errors by 1.31 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Final-text delay was not measured for one or both, so speed cannot be compared. Both are measured on the same 206 streamed turns.
Google Chirp 2 makes fewer errors on real conversations, and the two are not separated on speed. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.
Only Google Chirp 2. GPT-4o Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.
Cekura runs these simulated calls on your agent and scores every one.