ElevenLabs: Scribe v2 Medical

ElevenLabs Scribe v2 Medical is the batch speech-recognition edition specialized for medical and clinical audio. It is a fine-tune of Scribe v2, with recognition focused on medication names, anatomy, pathology and clinical dictation while retaining the general speech-transcription workflow. It converts the supplied recording into draft text with timing and optional speaker annotations. The maker’s intended uses are documentation and related administrative workflows, with the text reviewed and corrected before use.

Useful inputs include a recorded clinician-patient conversation, spoken dictation, an intake call or a care-coordination discussion. Preserve the original recording and enough surrounding speech to distinguish a term in context. Avoid clipping and keep meaningful speaker channels separate when the source provides them. The producer’s shared batch transcription interface accepts common audio formats such as WAV, MP3, FLAC and M4A. Medical terminology tuning improves the task focus; it does not reconstruct a clearly missing or inaudible part of the recording.

The manufacturer documents the same 90+ language support as Scribe v2. Its public medical-transcription information reports that medical accuracy improvements were measured in English, French and German. Those findings do not establish equal specialist-term performance in every supported language. Supply the known language when useful, retain names and code-switched terms, and review uncommon clinical vocabulary against the actual audio rather than accepting it because the sentence reads fluently.

The transcription output contains recognized text and timed words, with optional speaker labels and audio-event tags. Word start and end times make it possible to return to a medication name, a spoken quantity or a correction in the recording. A useful dictation artifact is therefore a transcript together with its word-aligned record. Review sensitive details in their full spoken context, including negations, uncertainty and the difference between something reported by a patient and something stated by the clinician.

For an ambient encounter, speaker diarization helps organize who spoke when. Treat an inferred label as a grouping of speech, then associate it with known roles or identities using the encounter record. Overlapping voices or similar-sounding speakers need particular attention when reviewing turn changes. If one speaker occupies each recording channel, the shared batch interface also provides independent channel transcription. Keep channel attribution distinct from diarization inferred from mixed audio, and retain the source layout when it helps review the result.

Keyterm prompting provides relevant words or phrases to guide recognition using context. Prepare a focused glossary from actual terminology expected in the recording, including proper spellings and abbreviations that matter to the documentation task. The maker’s batch guide allows up to 1,000 keyterms; they should be short and relevant rather than a comprehensive unrelated vocabulary. Inspect important terms at their timestamps. A supplied keyterm is a recognition hint, not evidence that the word was spoken and not an instruction to replace a different audible term.

The maker documents optional entity detection, including selected health-information categories, alongside the transcript. These annotations can help an authorized review process find relevant spans for correction or handling. The shared batch interface also offers entity redaction, which masks detected text with replacement labels; it requires entity detection, and the entity list is omitted when redaction is enabled. Keep the returned text and timing together with any annotations present in the selected result. A downstream edit, summary or extraction is a separate transformation of the transcript and should preserve the relationship to the recorded wording. For example, a tidied sentence should not erase a spoken correction or turn an uncertain statement into a definite finding.

The medical edition’s defined task is transcription. The manufacturer explicitly excludes interpretation of clinical information, diagnosis, treatment recommendations and clinical decision guidance from its intended purpose. For a finished documentation workflow, the relevant healthcare professional or authorized reviewer checks the draft against the recording and corrects important errors. The model supplies the text record to support that work; the transcript itself does not establish the correctness of a clinical statement or replace the review.

Keep the edition distinction clear when preparing a task. Scribe v2 Medical processes recorded audio; Scribe v2 Realtime is the separate live-transcription model. A medical fine-tune does not inherit speech-synthesis limits or capabilities merely because the same maker offers voice products. The useful result is a reviewed draft transcript with timing and speaker information suited to the recording, leaving inaudible or uncertain details visible for correction instead of silently filling them with plausible clinical language.