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Behavioral-health transcription turns therapy sessions and psychiatric intakes into accurate progress notes. AssemblyAI's Medical Mode, a one-parameter add-on to Universal-3.5 Pro, holds a 3.2% Missed Entity Rate on clinical conversations — the lowest across benchmarked providers — and speaker diarization separates clinician from client across a full session. BAA available.
Behavioral-health sessions are long, emotional, and full of medication names and clinical terms that general speech-to-text fumbles. Universal-3.5 Pro with Medical Mode captures the vocabulary — SSRIs, diagnoses, therapeutic modalities — so your progress-note layer works from a clean source. One parameter, async or realtime.
Missed Entity Rate on clinical conversations with Medical Mode.
Fewer missed medical entities than the base model without Medical Mode.
Fewer medical entity errors than the base model.
Lowest Missed Entity Rate vs. Deepgram, Speechmatics, AWS, and Google.
Missed Entity Rate is the share of clinical entities — medication names, dosages, diagnoses — that a model fails to transcribe correctly. Lower is better.
| Provider | Missed Entity Rate | Word Error Rate |
|---|---|---|
| AssemblyAI Universal-3.5 Pro w/ Medical Mode | 3.2% | 5.3% |
| Speechmatics Enhanced Medical | 3.6% | 5.5% |
| Deepgram Nova-3 Medical | 4.7% | 6.1% |
| AWS Transcribe Medical | 8.7% | 5.9% |
| Google Medical Conversation | 24.4% | 12.9% |
If you already transcribe with AssemblyAI, adding Medical Mode is a one-line change — async or realtime, no model swap and no re-integration.
import assemblyai as aai
aai.settings.api_key = "YOUR_API_KEY"
# Behavioral health: long sessions, psych meds, modalities
config = aai.TranscriptionConfig(
speech_models=["universal-3-5-pro", "universal-2"],
domain="medical-v1",
keyterms_prompt=["sertraline", "CBT", "generalized anxiety disorder", "SSRI"],
)
transcript = aai.Transcriber().transcribe("./therapy-session.wav", config)
print(transcript.text)Medication names, diagnoses, and modality terms (CBT, DBT, EMDR) land accurately so progress notes don't inherit transcription errors.
50-minute sessions, overlapping speech, and emotional cadence transcribed reliably, with optional diarization to separate clinician and client.
PHI redaction across audio and transcripts, BAA available, SOC 2 Type 2.
The note is only as good as the transcript underneath it. Medical Mode keeps drug names, dosages, and standardized assessment scores intact across a full session, so your DAP or SOAP generator drafts from an accurate record instead of correcting one.
Session transcript -> DAP progress note
D Client reports sleep improved to 6-7 hrs/night since
sertraline increased to 100 mg daily. Denies SI/HI.
PHQ-9 administered: 11 (down from 17 at intake).
A Moderate MDD, partial response to pharmacotherapy.
Sleep hygiene work appears to be holding.
P Continue sertraline 100 mg daily; reassess in 4 weeks.
Continue weekly CBT, thought-record homework.
Re-administer PHQ-9 at next session.
Entities Medical Mode has to hold: sertraline, 100 mg,
PHQ-9, MDD, CBT, SI/HI. A dropped dosage or a
transposed scale score changes the clinical record."In the medical context, accuracy is highly important. The biggest impact has been enabling our technical team to focus on workflow-specific features rather than a general speech-to-text pipeline."
Jackson Bierfeldt · Cofounder & CTO, JotPsych
"We've integrated the newest models from AssemblyAI for pre-recorded audio ASR in our ambient product, and it's been excellent. We're now exploring Universal-3.5 Pro for async and realtime speech-to-text capabilities for new use cases. What's been just as important is the reliability of the platform itself—both technically and in terms of partnership."
Gautam Pradeep · Tech Lead, Commure