Azure Speech To Text Rest Py

MicrosoftOfficialCreated by Microsoft

Skill
Tool integration
Data and AI
MIT
Low risk

From the author

Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK. Triggers: "speech to text REST", "short audio transcription", "speech recognition REST API", "STT REST", "recognize speech REST". DO NOT USE FOR: Long audio (>60 seconds), real-time streaming, batch transcription, custom speech models, speech translation. Use Speech SDK or Batch Transcription API instead.

— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a lightweight, SDK-free method to perform speech-to-text transcription using the Azure Speech to Text REST API. It is designed specifically for short audio clips (up to 60 seconds) and includes support for pronunciation assessment. By utilizing standard HTTP requests, it offers a straightforward integration path for developers needing basic speech recognition without the overhead of the full Azure Speech SDK.

What it does

Transcribes short audio files (up to 60 seconds) into text.
Supports pronunciation assessment with detailed scoring metrics.
Provides flexible output formats including simple and detailed JSON responses.
Enables chunked audio streaming for reduced latency.
Allows configuration of profanity filtering and language selection.
Supports authentication via subscription keys or Microsoft Entra tokens.

When to use it

When you need to transcribe short audio clips under 60 seconds.
When you want to avoid installing the full Azure Speech SDK.
When you need to evaluate pronunciation accuracy against reference text.
When building lightweight Python applications that require basic speech recognition.

Advantages

No SDK dependency; uses standard HTTP requests.
Supports both synchronous and asynchronous implementation patterns.
Provides granular pronunciation feedback including accuracy, fluency, and prosody.
Highly configurable output formats and profanity handling.

Usage examples

“Transcribe a 30-second WAV file using the Azure REST API.”: The agent will use the provided Python snippet to send the audio file to the Azure Speech endpoint and return the transcribed text.
“How do I check the pronunciation accuracy of a user saying 'Good morning'?”: The agent will demonstrate how to construct the Pronunciation-Assessment header with the reference text and interpret the returned accuracy and fluency scores.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/microsoft/azure-speech-to-text-rest-py/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip azure-speech-to-text-rest-py.zip -d .agents/skills

Documentation by Microsoft

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

Azure subscription - Create one free
Speech resource - Create in Azure Portal
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

Authentication & Lifecycle

🔑 Two rules apply to every code sample below:
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.
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

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

# 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)

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

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

# 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):

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

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

Files

ATTRIBUTION.mdAdded by AutoGineer995 B
LICENSELicence file added by AutoGineer1.1 KiB
SKILL.md11.8 KiB
references/pronunciation-assessment.md7.6 KiB

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Python

Security

What our scanner noticed· Low risk

Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by

Microsoft

Publisher

Microsoft (Official)

Source

microsoft/skills · .github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py · commit 0696600

Licence

MIT License (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-speech-to-text-rest-py.zip