Azure ai transcription py
/SKILLSDK Azure AI Transcription for Python. Use it for real-time and batch speech-to-text transcription, with timestamping and diarization.
--- name: azure-ai-transcription-py description: Azure AI TranscriptionSDKs for Python. Use it for real-time and batch speech-to-text transcription with timestamps and diarization. risk: unknown source: community date_added: '2026-02-27' --- # Azure AI Transcription SDK for Python Client library for Azure AI Transcription (speech-to-text) with real-time and batch transcription. ## Installation ``bash pip install azure-ai-transcription ` ## Environment Variables `bash TRANSCRIPTION_ENDPOINT=https://<resource>.cognitiveservices.azure.com TRANSCRIPTION_KEY=<your-key> ` ## Authentication Use subscription key authentication (DefaultAzureCredential is not supported for this client): `python import os from azure.ai.transcription import TranscriptionClient client = TranscriptionClient( endpoint=os.environ["TRANSCRIPTION_ENDPOINT"], credential=os.environ["TRANSCRIPTION_KEY"] ) ` ## Transcription (Batch) `python 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) `python 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 ## When to Use This skill is applicable for executing 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.
