Domain data
How is medical speech data collected in India?
Updated 2026-08-01 · 4 min read
Short answer
Medical speech collection in India requires clinician-grade terminology handling, stricter consent and PII treatment, and transcription by annotators trained on drug names, dosages, anatomy and abbreviations. The audio itself is often clinician dictation or doctor-patient conversation across a mix of English and a regional language, so code-mix handling is unavoidable. Accuracy thresholds are higher than for consumer speech because a substituted dosage is not a WER point, it is a safety event, and the annotation specification should treat numerals and drug names as separately measured categories.
Key takeaways
- Numerals and drug names need their own accuracy measurement, separate from overall WER.
- Doctor-patient audio is heavily code-mixed and needs a convention decided up front.
- Consent and de-identification requirements are stricter than for consumer speech.
What is collected
Clinician dictation, doctor-patient consultations, nursing handovers and tele-consultation audio, in English mixed with the regional language of the site.
Terminology and annotation
Transcribers need domain training and a controlled vocabulary for drug names, abbreviations and units. Measure accuracy separately on those categories; an overall WER of 8% can hide a 20% error rate on dosages.
Consent and de-identification
Patient consent, clinician consent and site permissions are separate. The specification must define whether patient identifiers are redacted from audio, masked in transcript or tagged, and the choice must match what was consented to.
Evaluation
Build the evaluation set from real consultation audio, not dictated scripts, and report per-category accuracy. Safety-critical categories deserve their own gate.
Frequently asked questions
How is medical speech data collected in India?
Medical speech collection in India requires clinician-grade terminology handling, stricter consent and PII treatment, and transcription by annotators trained on drug names, dosages, anatomy and abbreviations. The audio itself is often clinician dictation or doctor-patient conversation across a mix of English and a regional language, so code-mix handling is unavoidable. Accuracy thresholds are higher than for consumer speech because a substituted dosage is not a WER point, it is a safety event, and the annotation specification should treat numerals and drug names as separately measured categories.
What is collected?
Clinician dictation, doctor-patient consultations, nursing handovers and tele-consultation audio, in English mixed with the regional language of the site.
Terminology and annotation?
Transcribers need domain training and a controlled vocabulary for drug names, abbreviations and units. Measure accuracy separately on those categories; an overall WER of 8% can hide a 20% error rate on dosages.
Consent and de-identification?
Patient consent, clinician consent and site permissions are separate. The specification must define whether patient identifiers are redacted from audio, masked in transcript or tagged, and the choice must match what was consented to.
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