Awesome-omni-skill azure-ai-transcription-py
Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.
install
source · Clone the upstream repo
git clone https://github.com/diegosouzapw/awesome-omni-skill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/cli-automation/azure-ai-transcription-py" ~/.claude/skills/diegosouzapw-awesome-omni-skill-azure-ai-transcription-py && rm -rf "$T"
manifest:
skills/cli-automation/azure-ai-transcription-py/SKILL.mdsafety · automated scan (low risk)
This is a pattern-based risk scan, not a security review. Our crawler flagged:
- pip install
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source content
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
- Enable diarization when multiple speakers are present
- Use batch transcription for long files stored in blob storage
- Capture timestamps for subtitle generation
- Specify language to improve recognition accuracy
- Handle streaming backpressure for real-time transcription
- Close transcription sessions when complete
When to Use
This skill is applicable to execute the workflow or actions described in the overview.