Prompt

I need a speech-to-text API for medical dictation. What should I look at?

Artificial Intelligence / Speech & Voice AI1 observationLast seen Oct 11, 2026

Latest observation

Oct 11, 2026OpenAI APIWeb search: off

For medical dictation, you want more than “generic speech-to-text.” Look for an API that’s accurate with clinical terminology, secure enough for patient data, and easy to fit into your workflow.

Key things to evaluate

1. Medical/domain accuracy

Check whether the service is trained or tuned for:

  • Medical terminology
  • Drug names
  • Anatomy and procedures
  • Abbreviations/acronyms
  • Accent and noisy-environment robustness

Ask for:

  • Real medical benchmark results
  • Trial transcripts from your actual dictation style
  • Accuracy by specialty if relevant, like radiology, cardiology, or general practice

2. HIPAA / compliance

If you handle PHI, this is critical. Verify:

  • Whether the vendor will sign a BAA
  • HIPAA support
  • Data retention policies
  • Whether audio/transcripts are used for model training by default
  • Audit logs and admin controls

Also check any other regulatory needs depending on your region, like GDPR.

3. Security

Look for:

  • Encryption in transit and at rest
  • Strong access controls / IAM
  • SSO support
  • Role-based permissions
  • Audit trails
  • Region-specific data storage if required

4. Latency and workflow fit

Medical dictation often needs fast turnaround. Decide if you need:

  • Real-time streaming transcription
  • Batch transcription for recordings
  • Speaker diarization if multiple clinicians are involved
  • Punctuation/capitalization
  • Custom vocabulary or phrase boosting

5. Customization

Very useful for medical use cases:

  • Add custom terms, medication lists, provider names, facility names
  • Phrase hints / biasing
  • Custom models or fine-tuning, if offered
  • Post-processing rules for formatting notes

6. Output quality

Check if the API supports:

  • Word-level timestamps
  • Confidence scores
  • Alternative hypotheses
  • Structured output
  • Medical note formatting
  • Automatic paragraphing

7. Integration and developer experience

See whether it has:

  • Clean REST and/or streaming APIs
  • SDKs for your stack
  • Webhooks or callbacks
  • Good docs and examples
  • Versioning and backward compatibility

8. Cost and scaling

Compare:

  • Per-minute or per-hour pricing
  • Streaming vs batch rates
  • Extra charges for custom vocab, diarization, or storage
  • Enterprise minimums
  • Volume discounts

9. Reliability and support

For clinical workflows, support matters:

  • SLA / uptime guarantees
  • Enterprise support
  • Incident response process
  • Status page and historical uptime
  • Migration help and onboarding

Questions to ask vendors

  • Do you support HIPAA and BAAs?
  • Is customer audio/transcript data used for training?
  • Can we disable retention?
  • What’s the medical transcription accuracy on our specialty?
  • Can we add custom vocabulary?
  • Do you support real-time dictation?
  • Can we get timestamps, confidence scores, and speaker labels?
  • Where is data stored and processed?

Practical recommendation

Shortlist APIs that are:

  1. HIPAA-ready
  2. Strong on medical vocabulary
  3. Support custom terms
  4. Offer streaming if needed
  5. Have enterprise security controls

If you want, I can also help you compare specific vendors or make a checklist for evaluating them.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

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OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

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