Client library for Azure AI Transcription (speech-to-text) with real-time and batch transcription.
Scanned 6/6/2026
Install via CLI
openskills install frank-luongt/faos-skills-marketplace<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT -->
---
name: azure-ai-transcription-py
description: "Azure AI Transcription SDK for Python"
tags: [ai, azure]
---
# 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
<!-- Source: .faos/custom/skills/cloud/azure/ai-services/azure-ai-transcription-py/SKILL.md -->
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Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.