Azure Ai Transcription Py

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization. Triggers: "transcription", "speech to text", "Azure…

thegovind

@thegovind

What This Skill Does

Python SDK for Azure AI speech-to-text transcription. Supports both real-time streaming and batch processing of audio files, with speaker diarization and timestamp generation.

Replaces manual audio transcription workflows by providing a programmatic interface to Azure's speech recognition service with built-in diarization and timestamps.

When to Use It

  • Transcribe recorded meetings or calls with multiple speakers
  • Generate subtitles or captions from audio files
  • Stream live audio for real-time speech-to-text output
  • Process long audio files stored in Azure Blob Storage
  • Extract timestamped transcripts for search or analysis

Install

$ openclaw skills install @thegovind/azure-ai-transcription-py

Azure AI Transcription SDK for Python

Client library for Azure AI Transcription (speech-to-text) with real-time and batch transcription.

Installation

pip install azure-ai-transcription

Environment Variables

TRANSCRIPTION_ENDPOINT=https://<resource>.cognitiveservices.azure.com
TRANSCRIPTION_KEY=<your-key>

Authentication

Use subscription key authentication (DefaultAzureCredential is not supported for this client):

import os
from azure.ai.transcription import TranscriptionClient

client = TranscriptionClient(
    endpoint=os.environ["TRANSCRIPTION_ENDPOINT"],
    credential=os.environ["TRANSCRIPTION_KEY"]
)

Transcription (Batch)

job = client.begin_transcription(
    name="meeting-transcription",
    locale="en-US",
    content_urls=["https://<storage>/audio.wav"],
    diarization_enabled=True
)
result = job.result()
print(result.status)

Transcription (Real-time)

stream = client.begin_stream_transcription(locale="en-US")
stream.send_audio_file("audio.wav")
for event in stream:
    print(event.text)

Best Practices

  1. Enable diarization when multiple speakers are present
  2. Use batch transcription for long files stored in blob storage
  3. Capture timestamps for subtitle generation
  4. Specify language to improve recognition accuracy
  5. Handle streaming backpressure for real-time transcription
  6. Close transcription sessions when complete

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