Introducing Nova-3 Pharma: The First STT Model Purpose-Built for the Pharmaceutical Industry

Deepgram has introduced Nova-3 Pharma, a speech-to-text model designed specifically for pharmaceutical workflows in which accurately recognizing medication names is especially important for applications such as pharmacy IVRs, refill automation, contact-center agents, and clinical documentation. Built on the company’s medical speech foundation and trained on more than 5,000 drug names, the model aims to distinguish uncommon and phonetically similar pharmaceutical terms while retaining general transcription quality. In Deepgram’s benchmark using English medical audio from settings including telehealth, clinical dictation, and triage, Nova-3 Pharma ranked first among evaluated models for drug-name Keyword Recognition Rate, reporting 91.59% for batch transcription and 91.28% for streaming, and for lowest overall Word Error Rate, reporting 10.17% in batch and 11.69% in streaming. It is available through Deepgram’s hosted API and self-hosted deployments, supports batch and streaming transcription, and works across eight English language variants.

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