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 AI Transcription", "TranscriptionClient".
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install microsoft-skills-azure-ai-transcription-py
Repository
Skill path: .github/plugins/azure-sdk-python/skills/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 AI Transcription", "TranscriptionClient".
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Full Stack, Data / AI.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: microsoft.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install azure-ai-transcription-py into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/microsoft/skills before adding azure-ai-transcription-py to shared team environments
- Use azure-ai-transcription-py for development workflows
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Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
name: azure-ai-transcription-py
description: |
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 AI Transcription", "TranscriptionClient".
package: azure-ai-transcription
---
# 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