Compare speech-to-text models

Choose any two models to compare word error rate, time to first text, and final-text delay from the same recordings and test pipeline. Lower values are better for every displayed metric.

Accuracy depends on the audio and dataset. Use the Pipecat and Ocular word error rates separately, because a model can rank differently on clean clips and real conversations.

Yes. Select the tested Deepgram and AssemblyAI models to compare accuracy and streaming latency under the same conditions, including direct model-version comparisons.

Voice agents also depend on how quickly partial text arrives, how soon the final transcript is available after the speaker stops, whether text streams during speech, and whether the provider returns usable output consistently.