Add this skill
npx mdskills install sickn33/azure-speech-to-text-rest-pyComprehensive REST API skill with clear examples, error handling, and proper scope limitations
Simple REST API for speech-to-text transcription of short audio files (up to 60 seconds). No SDK required - just HTTP requests.
# Required
AZURE_SPEECH_KEY=
AZURE_SPEECH_REGION= # e.g., eastus, westus2, westeurope
# Alternative: Use endpoint directly
AZURE_SPEECH_ENDPOINT=https://.stt.speech.microsoft.com
pip install requests
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"])
| Format | Codec | Sample Rate | Notes |
|---|---|---|---|
| WAV | PCM | 16 kHz, mono | Recommended |
| OGG | OPUS | 16 kHz, mono | Smaller file size |
Limitations:
# WAV PCM 16kHz
"Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000"
# OGG OPUS
"Content-Type": "audio/ogg; codecs=opus"
params = {"language": "en-US", "format": "simple"}
{
"RecognitionStatus": "Success",
"DisplayText": "Remind me to buy 5 pencils.",
"Offset": "1236645672289",
"Duration": "1236645672289"
}
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"
}
]
}
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()
headers = {
"Ocp-Apim-Subscription-Key": os.environ["AZURE_SPEECH_KEY"]
}
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"
}
| 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) |
| Status | Description |
|---|---|
Success | Recognition succeeded |
NoMatch | Speech detected but no words matched |
InitialSilenceTimeout | Only silence detected |
BabbleTimeout | Only noise detected |
Error | Internal service error |
# 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"}
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
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"])
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) |
Use the Speech SDK or Batch Transcription API instead when you need:
| File | Contents |
|---|---|
| references/pronunciation-assessment.md | Pronunciation assessment parameters and scoring |
Install via CLI
npx mdskills install sickn33/azure-speech-to-text-rest-pyAzure Speech To Text REST Py is a free, open-source AI agent skill. |
Install Azure Speech To Text REST Py with a single command:
npx mdskills install sickn33/azure-speech-to-text-rest-pyThis downloads the skill files into your project and your AI agent picks them up automatically.
Azure Speech To Text REST Py works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Codex, Gemini Cli, Amp, Roo Code, Goose, Opencode, Trae, Qodo, Command Code. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.