Medical Conversation - Speech to Text

Convert medical conversations and healthcare dialogues to accurate text transcriptions with specialized processing for medical terminology, multi-speaker scenarios, and clinical documentation. Perfect for doctor-patient consultations, medical team discussions, and healthcare meetings.

Note: Audio files must first be uploaded using the Asset API before transcription. The audioUrl parameter should contain the path returned from the Asset API upload.

Supported Models

• medical_conversation: Specialized for medical conversations with enhanced medical terminology recognition and multi-speaker identification

Endpoint

POSThttps://api.1min.ai/api/features

Request Headers

Field	Value
API-KEY	<api-key>
Content-Type	application/json

Supported Audio Formats

• MP3 - MPEG Audio Layer III
• WAV - Waveform Audio File Format
• M4A - MPEG-4 Audio
• FLAC - Free Lossless Audio Codec
• MP4 - MPEG-4 Part 14 (audio only)
• WEBM - WebM Audio
• OGG - Ogg Vorbis

Language Support

The API supports various languages including:

• en-US - English (US)
• en-GB - English (UK)
• vi-VN - Vietnamese
• es-ES - Spanish
• fr-FR - French
• de-DE - German
• it-IT - Italian
• pt-PT - Portuguese
• ru-RU - Russian
• ja-JP - Japanese
• ko-KR - Korean
• zh-CN - Chinese (Simplified)
• ar-SA - Arabic

Note: For a complete list of all supported languages and their language codes, please refer to the Google Cloud Text-to-Speech documentation.

Parameters

Parameter	Type	Required	Description
type	string	Yes	Feature type, must be "SPEECH_TO_TEXT"
model	string	Yes	Model identifier, use "medical_conversation"
promptObject.audioUrl	string	Yes	Path to audio file (uploaded via Asset API)
promptObject.language	string	Yes	Language code for transcription (e.g., "en-US", "vi-VN")

Code Examples

cURL

curl --location 'https://api.1min.ai/api/features' \
--header 'API-KEY: <api-key>' \
--header 'Content-Type: application/json' \
--data '{
"type": "SPEECH_TO_TEXT",
"model": "medical_conversation",
"promptObject": {
  "audioUrl": "audios/2025_10_21_08_22_58_741_medical_conversation.m4a",
  "language": "en-US"
}
}'

JavaScript

fetch('https://api.1min.ai/api/features', {
method: 'POST',
headers: {
  'Content-Type': 'application/json',
  'API-KEY': 'YOUR_API_KEY'
},
body: JSON.stringify({
  type: 'SPEECH_TO_TEXT',
  model: 'medical_conversation',
  promptObject: {
    audioUrl: 'audios/2025_10_21_08_22_58_741_medical_conversation.m4a',
    language: 'en-US'
  }
})
})

Python

import requests

url = "https://api.1min.ai/api/features"
headers = {
"Content-Type": "application/json",
"API-KEY": "YOUR_API_KEY"
}

data = {
"type": "SPEECH_TO_TEXT",
"model": "medical_conversation",
"promptObject": {
  "audioUrl": "audios/2025_10_21_08_22_58_741_medical_conversation.m4a",
  "language": "en-US"
}
}

response = requests.post(url, headers=headers, json=data)

Interactive Playground

Try the API directly in your browser:

API Playground

GETPOSTPUTDELETEhttps://api.1min.ai/api/features

AI Model *Medical Conversation Model

Audio URL *

Path to the medical conversation audio file (upload via Asset API first)

Language *VietnameseEnglish (US)English (UK)SpanishFrenchGermanItalianPortugueseRussianJapaneseKoreanChinese (Simplified)Arabic

Generated cURL Command:

curl -X POST "https://api.1min.ai/api/features" \
  -H "API-KEY: <your-api-key>" \
  -H "Content-Type: application/json" \
  -d '{
  "type": "SPEECH_TO_TEXT",
  "model": "medical_conversation",
  "promptObject": {
    "audioUrl": "audios/2025_10_21_08_22_58_741_medical_conversation.m4a",
    "language": "en-US"
  }
}'

Use Cases

• Doctor-Patient Consultations: Transcribe medical appointments and clinical visits
• Medical Team Meetings: Document healthcare team discussions and case reviews
• Patient History Taking: Convert medical history interviews into structured text
• Clinical Rounds: Transcribe bedside discussions and patient presentations
• Telemedicine Sessions: Create records of virtual healthcare consultations
• Medical Training: Document educational conversations and clinical teaching
• Multidisciplinary Conferences: Transcribe complex medical team discussions
• Emergency Department Conversations: Capture critical communication in fast-paced environments

Tips for Best Results

1. Upload First: Use the Asset API to upload your audio file before transcription
2. Clear Audio Quality: Ensure all speakers are clearly audible with minimal background noise
3. Medical Context: The model is optimized for medical terminology and healthcare conversations
4. Multi-Speaker: Works best with 2-5 speakers in medical consultation scenarios
5. Language Selection: Choose the correct language for best medical terminology recognition
6. Audio Length: Optimal for conversations lasting 1-60 minutes
7. Speaker Positioning: Ensure all participants are positioned near the recording device

Error Handling

Common error scenarios and solutions:

• File not found: Ensure the audio file was uploaded via Asset API first
• Invalid audioUrl: Verify the path matches exactly what was returned from Asset API upload
• Language not supported: Check that the language code is in the supported list
• Poor audio quality: Medical conversations require clear audio for accurate transcription
• Too many speakers: Model works best with 2-5 speakers in medical settings

Response

The API returns a JSON response with the transcribed text from the medical conversation, including speaker identification and medical terminology recognition.