azure-ai-transcription-py

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

16 stars

Best use case

azure-ai-transcription-py is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

Teams using azure-ai-transcription-py should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/azure-ai-transcription-py/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/cli-automation/azure-ai-transcription-py/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/azure-ai-transcription-py/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How azure-ai-transcription-py Compares

Feature / Agentazure-ai-transcription-pyStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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 to execute the workflow or actions described in the overview.

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