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Use for real-time and batch speech-to-text transcription with timestamps and diarization.\n  Triggers: \"transcription\", \"speech to text\", \"Azure AI Transcription\", \"TranscriptionClient\".\npackage: azure-ai-transcription\n---\n\n# Azure AI Transcription SDK for Python\n\nClient library for Azure AI Transcription (speech-to-text) with real-time and batch transcription.\n\n## Installation\n\n```bash\npip install azure-ai-transcription\n```\n\n## Environment Variables\n\n```bash\nTRANSCRIPTION_ENDPOINT=https:\u002F\u002F\u003Cresource>.cognitiveservices.azure.com\nTRANSCRIPTION_KEY=\u003Cyour-key>\n```\n\n## Authentication\n\nUse subscription key authentication (DefaultAzureCredential is not supported for this client):\n\n```python\nimport os\nfrom azure.ai.transcription import TranscriptionClient\n\nclient = TranscriptionClient(\n    endpoint=os.environ[\"TRANSCRIPTION_ENDPOINT\"],\n    credential=os.environ[\"TRANSCRIPTION_KEY\"]\n)\n```\n\n## Transcription (Batch)\n\n```python\njob = client.begin_transcription(\n    name=\"meeting-transcription\",\n    locale=\"en-US\",\n    content_urls=[\"https:\u002F\u002F\u003Cstorage>\u002Faudio.wav\"],\n    diarization_enabled=True\n)\nresult = job.result()\nprint(result.status)\n```\n\n## Transcription (Real-time)\n\n```python\nstream = client.begin_stream_transcription(locale=\"en-US\")\nstream.send_audio_file(\"audio.wav\")\nfor event in stream:\n    print(event.text)\n```\n\n## Best Practices\n\n1. **Enable diarization** when multiple speakers are present\n2. **Use batch transcription** for long files stored in blob storage\n3. **Capture timestamps** for subtitle generation\n4. **Specify language** to improve recognition accuracy\n5. **Handle streaming backpressure** for real-time transcription\n6. **Close transcription sessions** when complete\n","# Azure AI Transcription SDK for Python\n\nClient library for Azure AI Transcription (speech-to-text) with real-time and batch transcription.\n\n## Installation\n\n```bash\npip install azure-ai-transcription\n```\n\n## Environment Variables\n\n```bash\nTRANSCRIPTION_ENDPOINT=https:\u002F\u002F\u003Cresource>.cognitiveservices.azure.com\nTRANSCRIPTION_KEY=\u003Cyour-key>\n```\n\n## Authentication\n\nUse subscription key authentication (DefaultAzureCredential is not supported for this client):\n\n```python\nimport os\nfrom azure.ai.transcription import TranscriptionClient\n\nclient = TranscriptionClient(\n    endpoint=os.environ[\"TRANSCRIPTION_ENDPOINT\"],\n    credential=os.environ[\"TRANSCRIPTION_KEY\"]\n)\n```\n\n## Transcription (Batch)\n\n```python\njob = client.begin_transcription(\n    name=\"meeting-transcription\",\n    locale=\"en-US\",\n    content_urls=[\"https:\u002F\u002F\u003Cstorage>\u002Faudio.wav\"],\n    diarization_enabled=True\n)\nresult = job.result()\nprint(result.status)\n```\n\n## Transcription (Real-time)\n\n```python\nstream = client.begin_stream_transcription(locale=\"en-US\")\nstream.send_audio_file(\"audio.wav\")\nfor event in stream:\n    print(event.text)\n```\n\n## Best Practices\n\n1. **Enable diarization** when multiple speakers are present\n2. **Use batch transcription** for long files stored in blob storage\n3. **Capture timestamps** for subtitle generation\n4. **Specify language** to improve recognition accuracy\n5. **Handle streaming backpressure** for real-time transcription\n6. **Close transcription sessions** when complete\n",{"name":5,"package":40,"description":41},"azure-ai-transcription","Azure AI Transcription SDK for Python. 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