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🛠️ Azure音声ToテキストRestPy

azure-speech-to-text-rest-py

Microsoft Azureの音声認識サービスを使い、最長6

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📜 元の英語説明(参考)

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.

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Microsoft Azureの音声認識サービスを使い、最長6

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最終更新
2026-05-17
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2026-05-17
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💬 こう話しかけるだけ — サンプルプロンプト

  • Azure Speech To Text Rest Py を使って、最小構成のサンプルコードを示して
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📖 Claude が読む原文 SKILL.md(中身を展開)

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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

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
"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

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

  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

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

When to Use

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

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.