azure-speech-to-text-rest-py
Perform quick audio transcription using the Azure Speech REST API.
Install
mkdir -p .claude/skills/azure-speech-to-text-rest-py && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/7754" && unzip -o skill.zip -d .claude/skills/azure-speech-to-text-rest-py && rm skill.zipInstalls to .claude/skills/azure-speech-to-text-rest-py
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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.Key capabilities
- →Transcribe short audio files via REST API
- →Support WAV and OGG audio formats
- →Stream audio chunks for lower latency
- →Handle authentication via subscription keys or tokens
- →Configure language and profanity settings
How it works
The skill sends HTTP POST requests to the Azure Speech REST API, supporting both full file uploads and chunked streaming for short audio transcription.
Inputs & outputs
When to use azure-speech-to-text-rest-py
- →Transcribe short audio clips
- →Extract text from brief voice recordings
- →Automate basic speech recognition
About this skill
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-Keyheader) for quick access, or a Microsoft Entra token (including one acquired withDefaultAzureCredential) via theAuthorizationrequest 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 |
Content truncated.
When not to use it
- →For audio longer than 60 seconds
- →For real-time streaming or batch transcription
- →For custom speech models or translation
Prerequisites
Limitations
- →Maximum 60 seconds of audio
- →No partial or interim results
- →Requires specific audio formats (WAV/OGG)
How it compares
This provides a lightweight REST-based alternative to the full Azure Speech SDK for simple, short-duration transcription tasks.
Compared to similar skills
azure-speech-to-text-rest-py side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| azure-speech-to-text-rest-py (this skill) | 1 | 29d | Caution | Beginner |
| langchain-architecture | 8 | 2mo | Review | Intermediate |
| voice-ai-development | 5 | 6mo | No flags | Advanced |
| python-sdk | 4 | 3mo | No flags | Intermediate |
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