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Speech-to-Text offers two medical models in addition the other
standard and enhanced speech recognition models.
The medical models are specifically tailored for recognition of words that
are common in medical settings, such as diagnoses, medications, symptoms,
treatments, and conditions. If you want to recognize this type of audio data,
you can improve your transcription results by using these models.
There are two medical models, each tailored to specific use cases:
medical_conversation: for conversations between a medical
providerโfor example, a doctor or nurseโand a patient. Use this model
when both a provider and a patient are speaking. Words
uttered by each speaker are automatically detected and labeled in the
returned transcript.
medical_dictation: for dictated notes spoken by a single medical
providerโfor example, a doctor dictating notes about a patient's
blood test results.
Use medical models only with the following Speech-to-Text features. Features
omitted from this list can't be used with either medical model. The automatic
punctuation feature is enabled by default.
You should receive a JSON response similar to the following:
"results": [
{
"alternatives": [
{
"transcript": "Um-hum . Yeah. Hello , good morning . Good
morning . So , tell me what's going on . Uh , sure , so , um , I
woke up probably three or four days ago , which , uh , wheezing and short of breath .
Okay , any cough or chest pain ? I cough infrequently , but no ,
uh , chest pain . Have you been exposed to anyone with covid ?
Uh , no , and I also took a test , which was negative . Uh , is it getting
worse , or better ? Uh , it has been getting a lot worse"
}
]
},
{
"alternatives": [
{
"transcript": "Okay . Was there something that triggered this exposure to cold , for
example ? Um , I had a gone hiking , and I got caught in the rain the day
before this all started ."
}
]
}
]
}
Spoken punctuation
The medical dictation model supports spoken punctuation for medical notes. This
feature is enabled by default, and cannot be disabled. Spoken punctuation is
delineated by brackets in the speech transcription. For example, your returned
transcription might look similar to the following:
Patient could be showing signs of trauma [question mark] They said they were [quote] having elevated heart rate [unquote].
Speech-to-Text supports the following spoken punctuation:
period
comma
colon
caps
slash
dash
hyphen
question mark
semicolon
quote
unquote
end quote
open parenthesis
close parenthesis
end parenthesis
Formatting commands
The medical dictation model supports spoken commands for formatting notes. This
feature is enabled by default, and cannot be disabled. The spoken commands will
be delineated by brackets in the speech transcription. For example, your
returned transcription might look similar to the following:
[next line] Patient says they are experiencing fever [next point].
Speech-to-Text supports the following spoken commands:
next point
next number
next paragraph
caps
capitalization
new line
next item
next problem
next problem number
next row
next section
number next
scratch
scratch that
end dictation
Spoken headings
The medical dictation model supports spoken headings for dictated notes. This
feature is enabled by default, and cannot be disabled. The headings will be
delineated by brackets in the transcription and will be capitalized. For
example, your returned transcription might look similar to the following:
[CURRENT MEDICATIONS] Patient is currently taking no medications.
Speech-to-Text supports the following spoken headings:
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-29 UTC."],[],[],null,["# Recognize speech by using medical models\n\nSpeech-to-Text offers two *medical* models in addition the other\n[standard and enhanced speech recognition models](https://cloud.google.com/speech-to-text/docs/transcription-model).\nThe medical models are specifically tailored for recognition of words that\nare common in medical settings, such as diagnoses, medications, symptoms,\ntreatments, and conditions. If you want to recognize this type of audio data,\nyou can improve your transcription results by using these models.\n\nThere are two medical models, each tailored to specific use cases:\n\n- `medical_conversation`: for conversations between a medical provider---for example, a doctor or nurse---and a patient. Use this model when both a provider and a patient are speaking. Words uttered by each speaker are automatically detected and labeled in the returned transcript.\n- `medical_dictation`: for dictated notes spoken by a single medical provider---for example, a doctor dictating notes about a patient's blood test results.\n\nUse medical models only with the following Speech-to-Text features. Features\nomitted from this list can't be used with either medical model. The automatic\npunctuation feature is enabled by default.\n\n- [Automatic punctuation](/speech-to-text/docs/automatic-punctuation)\n- [Alternate transcriptions](/speech-to-text/docs/speech-to-text-requests#selecting_alternatives)\n- [Word timestamps](/speech-to-text/docs/async-time-offsets)\n- [Word-level confidence](/speech-to-text/docs/word-confidence)\n\nThe medical conversation model supports the following features:\n\n- [Speaker diarization](/speech-to-text/docs/multiple-voices)\n\nThe medical dictation model supports the following features:\n\n- [Spoken Punctuation](#spoken_punctuation)\n- [Formatting Commands](#formatting_commands)\n- [Spoken Headings](#spoken_headings)\n\nSend a transcription request\n----------------------------\n\n### REST\n\nThe following code sample uses the `medical_conversation` model to transcribe\nan audio file in a public Cloud Storage bucket.\n\n\nBefore using any of the request data,\nmake the following replacements:\n\n- \u003cvar translate=\"no\"\u003eLANGUAGE_CODE\u003c/var\u003e: the BCP-47 code of the language spoken in your audio clip. Medical models are only available for *en-US*.\n- \u003cvar translate=\"no\"\u003eENCODING\u003c/var\u003e: the encoding of the audio you want to transcribe. If you are using the public audio sample, the encoding is `LINEAR16`.\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: the alphanumeric ID of your Google Cloud project.\n\n\nHTTP method and URL:\n\n```\nPOST https://speech.googleapis.com/v1/speech:recognize\n```\n\n\nRequest JSON body:\n\n```\n{\n \"config\": {\n \"languageCode\": \"LANGUAGE_CODE\",\n \"encoding\": \"ENCODING\",\n \"model\": \"medical_conversation\"\n },\n \"audio\": {\n \"uri\": \"gs://cloud-samples-data/speech/medical_conversation_2.wav\"\n }\n}\n```\n\nTo send your request, expand one of these options:\n\n#### curl (Linux, macOS, or Cloud Shell)\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) , or by using [Cloud Shell](/shell/docs), which automatically logs you into the `gcloud` CLI . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nSave the request body in a file named `request.json`,\nand execute the following command:\n\n```\ncurl -X POST \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n -H \"x-goog-user-project: PROJECT_ID\" \\\n -H \"Content-Type: application/json; charset=utf-8\" \\\n -d @request.json \\\n \"https://speech.googleapis.com/v1/speech:recognize\"\n```\n\n#### PowerShell (Windows)\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nSave the request body in a file named `request.json`,\nand execute the following command:\n\n```\n$cred = gcloud auth print-access-token\n$headers = @{ \"Authorization\" = \"Bearer $cred\"; \"x-goog-user-project\" = \"PROJECT_ID\" }\n\nInvoke-WebRequest `\n -Method POST `\n -Headers $headers `\n -ContentType: \"application/json; charset=utf-8\" `\n -InFile request.json `\n -Uri \"https://speech.googleapis.com/v1/speech:recognize\" | Select-Object -Expand Content\n```\n\nYou should receive a JSON response similar to the following:\n\n```\n \"results\": [\n {\n \"alternatives\": [\n {\n \"transcript\": \"Um-hum . Yeah. Hello , good morning . Good\n morning . So , tell me what's going on . Uh , sure , so , um , I\n woke up probably three or four days ago , which , uh , wheezing and short of breath .\n Okay , any cough or chest pain ? I cough infrequently , but no ,\n uh , chest pain . Have you been exposed to anyone with covid ?\n Uh , no , and I also took a test , which was negative . Uh , is it getting\n worse , or better ? Uh , it has been getting a lot worse\"\n }\n ]\n },\n {\n \"alternatives\": [\n {\n \"transcript\": \"Okay . Was there something that triggered this exposure to cold , for\n example ? Um , I had a gone hiking , and I got caught in the rain the day\n before this all started .\"\n }\n ]\n }\n ]\n}\n```\n\n\u003cbr /\u003e\n\nSpoken punctuation\n------------------\n\nThe medical dictation model supports spoken punctuation for medical notes. This\nfeature is enabled by default, and cannot be disabled. Spoken punctuation is\ndelineated by brackets in the speech transcription. For example, your returned\ntranscription might look similar to the following:\n\n`Patient could be showing signs of trauma [question mark] They said they were [quote] having elevated heart rate [unquote]`.\n\nSpeech-to-Text supports the following spoken punctuation:\n\n- period\n- comma\n- colon\n- caps\n- slash\n- dash\n- hyphen\n- question mark\n- semicolon\n- quote\n- unquote\n- end quote\n- open parenthesis\n- close parenthesis\n- end parenthesis\n\nFormatting commands\n-------------------\n\nThe medical dictation model supports spoken commands for formatting notes. This\nfeature is enabled by default, and cannot be disabled. The spoken commands will\nbe delineated by brackets in the speech transcription. For example, your\nreturned transcription might look similar to the following:\n\n`[next line] Patient says they are experiencing fever [next point]`.\n\nSpeech-to-Text supports the following spoken commands:\n\n- next point\n- next number\n- next paragraph\n- caps\n- capitalization\n- new line\n- next item\n- next problem\n- next problem number\n- next row\n- next section\n- number next\n- scratch\n- scratch that\n- end dictation\n\nSpoken headings\n---------------\n\nThe medical dictation model supports spoken headings for dictated notes. This\nfeature is enabled by default, and cannot be disabled. The headings will be\ndelineated by brackets in the transcription and will be capitalized. For\nexample, your returned transcription might look similar to the following:\n\n`[CURRENT MEDICATIONS] Patient is currently taking no medications`.\n\nSpeech-to-Text supports the following spoken headings:\n\n- CHIEF COMPLAINT\n- CURRENT MEDICATIONS\n- DISCHARGE MEDICATIONS\n- DISCHARGE PLAN\n- FAMILY HISTORY\n- FINDINGS\n- REVIEW OF SYSTEMS\n- HISTORY OF PRESENT ILLNESS\n- INDICATIONS\n- LABS\n- PAST SURGICAL HISTORY\n- PHYSICAL EXAM\n- REVIEW OF SYSTEMS\n- RADIOLOGY"]]