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.
", "aboutText": "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.\n\nUseful 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.\n\nThe 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.\n\nThe 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.\n\nFor 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.\n\nKeyterm 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.\n\nThe 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.\n\nThe 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.\n\nKeep 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.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "e851d8572bf0d87e46fc049d2c45c3c4d03e0dafddee739c03285918024cfa7f", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "en", "methods": [ { "html": "elevenlabs/scribe-v2-medicalElevenLabs Scribe v2 Medical transcribes recorded clinical audio with vocabulary tuning for medication names, anatomy and pathology. It supports 90+ languages, word timing, speaker diarization and contextual keyterms. Its output is a reviewable draft transcript for documentation, rather than clinical interpretation.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
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.
POST /v1/audio/transcriptionsaudiotext| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits elevenlabs/scribe-v2-medical | Default— |
Fieldinput_audio | Typeobject | RequirementRequired | Values & limits | Default— |
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, input_audio |
Parametermaterial_types | Contractaudio |
Parametermaterial_conditions | ContractThe example reads your actual nonempty PCM WAV file, encodes the complete file bytes as base64 and sends input_audio.format as wav. |
Lifecycle: synchronous_result_then_owned_library
GET /v1/media/tasks/{task_id} · exact task_id from an existing owned media record
GET /v1/media/assets/{asset_id}/content
GET /v1/media/assets
GET /v1/media/assets/{asset_id}
Tariff references do not add request options. Supported parameters are listed for the selected method.
Match each charge to the conditions shown. Use one rate for each set of alternative configurations.
| Configuration | Rate schedule | Billing unit | Charge |
|---|---|---|---|
| ConfigurationBase token rates | Rate scheduleBase rate | Billing unit— | Charge Input · Input tokens — / 1K tokens Output · Output tokens — / 1K tokens Input · Cache read — / 1K tokens Input · Cache write — / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
| Configurationinput audio second | Rate schedule— | Billing unitper input audio second | Charge Input · input audio second $0.0001222222222222 per input audio second |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_AUDIO_FILE:?Set the path to your actual PCM WAV recording}"\nexport AILOOT_AUDIO_FILE\npython3 - <<'PY_REQUEST'\nimport base64, io, json, os, wave\nfrom pathlib import Path\naudio = Path(os.environ['AILOOT_AUDIO_FILE']).read_bytes()\nif not (audio[:4] == b'RIFF' and audio[8:12] == b'WAVE'):\n raise SystemExit('Supply your actual PCM WAV audio file')\nwith wave.open(io.BytesIO(audio), 'rb') as recording:\n if recording.getcomptype() != 'NONE' or recording.getnframes() <= 0:\n raise SystemExit('Supply a nonempty PCM WAV recording')\nrequest = {'model': 'elevenlabs/scribe-v2-medical', 'input_audio': {'data': base64.b64encode(audio).decode('ascii'), 'format': 'wav'}}\nPath('request.json').write_text(json.dumps(request, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o response.bin\n# Retain the complete original response, headers and actual X-Client-Request-ID.\n# Read existing owned records for recovery; do not resubmit an uncertain operation.\nComplete original response body, status and forwarded headers. No universal JSON shape, text field or task envelope is added by this handler.
GET /v1/media/tasks/{task_id}GET /v1/media/assets/{asset_id}/contentGET /v1/media/assetsGET /v1/media/assets/{asset_id}Keep every complete returned response, file and content part.
Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.
Retain the actual X-Client-Request-ID and complete response. Read the original owned assets and their exact signed content URLs; never resubmit an uncertain creation.
| Field | Type |
|---|---|
Fieldtext (when present) | Type |
Fieldusage (when present) | Type |
| Response | Condition | Next step |
|---|---|---|
Response400 · invalid_request_error | ConditionThe JSON body or explicit canonical model ID is invalid. | Next stepRetain the response and correct the indicated request field. |
Response401 · authentication_error | ConditionThe Ailoot API key is invalid. | Next stepUse your authorized Ailoot API key. |
Response403 · permission_error | ConditionThe key group does not admit this method. | Next stepRetain the returned error details. |
Response404 · not_found_error | ConditionThe selected method has no admitted route. | Next stepRetain the returned error details. |
Response422 · price_unavailable | ConditionThe accepted tariff cannot obtain its required input quantity or bound. | Next stepRetain the response; use the input representation required by the accepted tariff. |
Response503 · | ConditionRequired storage, route, method price or reservation is unavailable. | Next stepKeep the complete original response. An uncertain reservation is not permission to resubmit. |
Response502 · server_error | ConditionThe original result, usage or settlement requires checking. | Next stepRetain the actual request ID and original response. Read the existing owned record; do not resubmit creation. |
Ailoot Ultra elevenlabs/scribe-v2-medical
Use the method paths shown above.