Azure Speech to Text REST API for Short Audio

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

# 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

pip install requests

Quick Start

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

Limitations:

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

Content-Type Headers

# WAV PCM 16kHz
"Content-Type": "audio/​wav; codecs=audio/​pcm; samplerate=16000"

# OGG OPUS
"Content-Type": "audio/​ogg; codecs=opus"

Response Formats

Simple Format (default)

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

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

Detailed Format

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

{
  "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:

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)

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

Option 2: Bearer Token

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

Recognition Status Values

Profanity Handling

# 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

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

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):

Best Practices

1. Use WAV PCM 16kHz mono for best compatibility
2. Enable chunked transfer for lower latency
3. Cache access tokens for 9 minutes (valid for 10)
4. Specify the correct language for accurate recognition
5. Use detailed format when you need confidence scores
6. 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

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

---

<!-- AGI-INTEGRATION-START -->

AGI Framework Integration

Adapted for @techwavedev/​agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior API design decisions, database schema choices, and error handling patterns. Cache API response templates for consistent error formatting.

# Check for prior backend/​API context before starting
python3 execution/​memory_manager.py auto --query "API design patterns and architecture decisions for Azure Speech To Text Rest Py"

Storing Results

After completing work, store backend/​API decisions for future sessions:

python3 execution/​memory_manager.py store \
  --content "API architecture: REST with HATEOAS, JWT auth, rate limiting at 100 req/​min per tenant" \
  --type decision --project <project> \
  --tags azure-speech-to-text-rest-py backend

Multi-Agent Collaboration

Share API contract changes with frontend agents so they update their client code, and with QA agents for test coverage.

python3 execution/​cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Implemented API endpoints — 5 new routes with OpenAPI spec and integration tests" \
  --project <project>

Agent Team: Code Review

After implementation, dispatch code_review_team for two-stage review (spec compliance + code quality) before merging.

<!-- AGI-INTEGRATION-END -->