Azure Speech to Text REST API for Short Audio

Simple REST API for speech-to-text transcription of short audio files (up to 60 seconds). No SDK required - just HTTP requests.

Prerequisites

1. Azure subscription - Create one free
2. Speech resource - Create in Azure Portal
3. Get credentials - After deployment, go to resource > Keys and Endpoint

Environment Variables

bash
# Required
AZURE_SPEECH_KEY=<your-speech-resource-key>
AZURE_SPEECH_REGION=<region>  # e.g., eastus, westus2, westeurope

# Alternative: Use endpoint directly
AZURE_SPEECH_ENDPOINT=https://<region>.stt.speech.microsoft.com

Installation

bash
pip install requests

Authentication & Lifecycle

> 🔑 Two rules apply to every code sample below: > > 1. Two auth modes are supported. Use a subscription key (Ocp-Apim-Subscription-Key header) for quick access, or a Microsoft Entra token (including one acquired with DefaultAzureCredential) via the Authorization request header (see "Option 2" below). Never hardcode credentials in source. > 2. Use context managers for files and HTTP resources so file handles and network connections are released deterministically: > - Sync: with open(...) as f: and (when reusing connections) with requests.Session() as session: > - Async: async with aiohttp.ClientSession() as session: > > Snippets may abbreviate this setup, but production code should always follow both rules.

Quick Start

python
import os
import requests

def transcribe_audio(audio_file_path: str, language: str = "en-US") -> dict:
    """Transcribe short audio file (max 60 seconds) using REST API."""
    region = os.environ["AZURE_SPEECH_REGION"]
    api_key = os.environ["AZURE_SPEECH_KEY"]
    
    url = f"https://{region}.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1"
    
    headers = {
        "Ocp-Apim-Subscription-Key": api_key,
        "Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
        "Accept": "application/json"
    }
    
    params = {
        "language": language,
        "format": "detailed"  # or "simple"
    }
    
    with open(audio_file_path, "rb") as audio_file:
        response = requests.post(url, headers=headers, params=params, data=audio_file)
    
    response.raise_for_status()
    return response.json()

# Usage
result = transcribe_audio("audio.wav", "en-US")
print(result["DisplayText"])

Audio Requirements

| Format | Codec | Sample Rate | Notes | |--------|-------|-------------|-------| | WAV | PCM | 16 kHz, mono | Recommended | | OGG | OPUS | 16 kHz, mono | Smaller file size |

Limitations:

• Maximum 60 seconds of audio
• For pronunciation assessment: maximum 30 seconds
• No partial/interim results (final only)

Content-Type Headers

python
# WAV PCM 16kHz
wav_headers = {
    "Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000"
}

# OGG OPUS
ogg_headers = {
    "Content-Type": "audio/ogg; codecs=opus"
}

Response Formats

Simple Format (default)

python
params = {"language": "en-US", "format": "simple"}

json
{
  "RecognitionStatus": "Success",
  "DisplayText": "Remind me to buy 5 pencils.",
  "Offset": "1236645672289",
  "Duration": "1236645672289"
}

Detailed Format

python
params = {"language": "en-US", "format": "detailed"}

json
{
  "RecognitionStatus": "Success",
  "Offset": "1236645672289",
  "Duration": "1236645672289",
  "NBest": [
    {
      "Confidence": 0.9052885,
      "Display": "What's the weather like?",
      "ITN": "what's the weather like",
      "Lexical": "what's the weather like",
      "MaskedITN": "what's the weather like"
    }
  ]
}

Chunked Transfer (Recommended)

For lower latency, stream audio in chunks:

python
import os
import requests

def transcribe_chunked(audio_file_path: str, language: str = "en-US") -> dict:
    """Stream audio in chunks for lower latency."""
    region = os.environ["AZURE_SPEECH_REGION"]
    api_key = os.environ["AZURE_SPEECH_KEY"]
    
    url = f"https://{region}.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1"
    
    headers = {
        "Ocp-Apim-Subscription-Key": api_key,
        "Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
        "Accept": "application/json",
        "Transfer-Encoding": "chunked",
        "Expect": "100-continue"
    }
    
    params = {"language": language, "format": "detailed"}
    
    def generate_chunks(file_path: str, chunk_size: int = 1024):
        with open(file_path, "rb") as f:
            while chunk := f.read(chunk_size):
                yield chunk
    
    response = requests.post(
        url, 
        headers=headers, 
        params=params, 
        data=generate_chunks(audio_file_path)
    )
    
    response.raise_for_status()
    return response.json()

Authentication Options

Option 1: Subscription Key (Simple)

python
headers = {
    "Ocp-Apim-Subscription-Key": os.environ["AZURE_SPEECH_KEY"]
}

Option 2: Bearer Token

python
import requests
import os

def get_access_token() -> str:
    """Get access token from the token endpoint."""
    region = os.environ["AZURE_SPEECH_REGION"]
    api_key = os.environ["AZURE_SPEECH_KEY"]
    
    token_url = f"https://{region}.api.cognitive.microsoft.com/sts/v1.0/issueToken"
    
    response = requests.post(
        token_url,
        headers={
            "Ocp-Apim-Subscription-Key": api_key,
            "Content-Type": "application/x-www-form-urlencoded",
            "Content-Length": "0"
        }
    )
    response.raise_for_status()
    return response.text

# Use token in requests (valid for 10 minutes)
token = get_access_token()
headers = {
    "Authorization": f"Bearer {token}",
    "Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
    "Accept": "application/json"
}

Query Parameters

| Parameter | Required | Values | Description | |-----------|----------|--------|-------------| | language | Yes | en-US, de-DE, etc. | Language of speech | | format | No | simple, detailed | Result format (default: simple) | | profanity | No | masked, removed, raw | Profanity handling (default: masked) |

Recognition Status Values

| Status | Description | |--------|-------------| | Success | Recognition succeeded | | NoMatch | Speech detected but no words matched | | InitialSilenceTimeout | Only silence detected | | BabbleTimeout | Only noise detected | | Error | Internal service error |

Profanity Handling

python
# Mask profanity with asterisks (default)
params = {"language": "en-US", "profanity": "masked"}

# Remove profanity entirely
params = {"language": "en-US", "profanity": "removed"}

# Include profanity as-is
params = {"language": "en-US", "profanity": "raw"}

Error Handling

python
import requests

def transcribe_with_error_handling(audio_path: str, language: str = "en-US") -> dict | None:
    """Transcribe with proper error handling."""
    region = os.environ["AZURE_SPEECH_REGION"]
    api_key = os.environ["AZURE_SPEECH_KEY"]
    
    url = f"https://{region}.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1"
    
    try:
        with open(audio_path, "rb") as audio_file:
            response = requests.post(
                url,
                headers={
                    "Ocp-Apim-Subscription-Key": api_key,
                    "Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
                    "Accept": "application/json"
                },
                params={"language": language, "format": "detailed"},
                data=audio_file
            )
        
        if response.status_code == 200:
            result = response.json()
            if result.get("RecognitionStatus") == "Success":
                return result
            else:
                print(f"Recognition failed: {result.get('RecognitionStatus')}")
                return None
        elif response.status_code == 400:
            print(f"Bad request: Check language code or audio format")
        elif response.status_code == 401:
            print(f"Unauthorized: Check API key or token")
        elif response.status_code == 403:
            print(f"Forbidden: Missing authorization header")
        else:
            print(f"Error {response.status_code}: {response.text}")
        
        return None
        
    except requests.exceptions.RequestException as e:
        print(f"Request failed: {e}")
        return None

Async Version

python
import os
import aiohttp
import asyncio

async def transcribe_async(audio_file_path: str, language: str = "en-US") -> dict:
    """Async version using aiohttp."""
    region = os.environ["AZURE_SPEECH_REGION"]
    api_key = os.environ["AZURE_SPEECH_KEY"]
    
    url = f"https://{region}.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1"
    
    headers = {
        "Ocp-Apim-Subscription-Key": api_key,
        "Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
        "Accept": "application/json"
    }
    
    params = {"language": language, "format": "detailed"}
    
    async with aiohttp.ClientSession() as session:
        with open(audio_file_path, "rb") as f:
            audio_data = f.read()
        
        async with session.post(url, headers=headers, params=params, data=audio_data) as response:
            response.raise_for_status()
            return await response.json()

# Usage
result = asyncio.run(transcribe_async("audio.wav", "en-US"))
print(result["DisplayText"])

Supported Languages

Common language codes (see full list):

| Code | Language | |------|----------| | en-US | English (US) | | en-GB | English (UK) | | de-DE | German | | fr-FR | French | | es-ES | Spanish (Spain) | | es-MX | Spanish (Mexico) | | zh-CN | Chinese (Mandarin) | | ja-JP | Japanese | | ko-KR | Korean | | pt-BR | Portuguese (Brazil) |

Best Practices

1. Pick sync OR async and stay consistent. Do not mix azure.xxx sync clients with azure.xxx.aio async clients in the same call path. Choose one mode per module.
2. Use context managers for files and HTTP resources. Use with open(...) as f: and (when reusing connections) with requests.Session() as session: for sync code, or async with aiohttp.ClientSession() as session: for async code.
3. Use WAV PCM 16kHz mono for best compatibility
4. Enable chunked transfer for lower latency
5. Cache access tokens for 9 minutes (valid for 10)
6. Specify the correct language for accurate recognition
7. Use detailed format when you need confidence scores
8. Handle all RecognitionStatus values in production code

When NOT to Use This API

Use the Speech SDK or Batch Transcription API instead when you need:

• Audio longer than 60 seconds
• Real-time streaming transcription
• Partial/interim results
• Speech translation
• Custom speech models
• Batch transcription of many files

Reference Files

| File | Contents | |------|----------| | references/pronunciation-assessment.md | Pronunciation assessment parameters and scoring |