GPT-4o Transcribe vs Speechmatics Linden
Accuracy and speed
Left gets fewer words wrong. Lower has the final text ready sooner.
- 4o Transcribe3.90% · 652ms
- Linden2.46% · 147ms
Speechmatics Linden is ahead of GPT-4o Transcribe on both datasets together, the Pipecat Dataset, the Ocular Dataset and final-text delay.
Last updated Methodology by Dileep Chagam
Who is better at what
- Overall WER6.85%2.97%
- Pipecat Dataset WER3.90%2.46%
- Ocular Dataset WER12.45%3.93%
- Time to first textn/a1.19s
- Final-text delay652ms147ms
Lower is better on every measure. Too close to call means the likely ranges overlap. Our guide covers testing OpenAI Realtime API voice agents.
4o Transcribe vs Linden FAQ
Which is more accurate, GPT-4o Transcribe or Speechmatics Linden?
Speechmatics Linden is more accurate on both datasets. On the 1,000 public Pipecat clips, GPT-4o Transcribe scores 6.85% and Speechmatics Linden 2.97%, so Speechmatics Linden makes fewer errors by 3.89 points. On the eight licensed Ocular recordings, GPT-4o Transcribe scores 3.90% and Speechmatics Linden 2.46%, so Speechmatics Linden makes fewer errors by 1.45 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Speechmatics Linden is more accurate on both datasets. On the 1,000 public Pipecat clips, GPT-4o Transcribe scores 6.85% and Speechmatics Linden 2.97%, so Speechmatics Linden makes fewer errors by 3.89 points. On the eight licensed Ocular recordings, GPT-4o Transcribe scores 3.90% and Speechmatics Linden 2.46%, so Speechmatics Linden makes fewer errors by 1.45 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.
Speechmatics Linden 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 Speechmatics Linden. GPT-4o Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.
Test your voice agent the same way.
Cekura runs these simulated calls on your agent and scores every one.