azure-ai-transcription-py

Name: azure-ai-transcription-py
Availability: InStock
Author: Microsoft

Convert speech to text with Azure AI Transcription for streaming and batch workflows.

2.9k|323|Updated Jan 16, 2026

Search Tags:#python #azure #real-time #transcription #batch #speech-to-text #diarization

Ready to run

npx skills add https://github.com/microsoft/skills --skill azure-ai-transcription-py-microsoft

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: azure-ai-transcription-py
Source: https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-ai-transcription-py
Command: npx skills add https://github.com/microsoft/skills --skill azure-ai-transcription-py-microsoft

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Python applications can convert spoken language into text using Azure AI Transcription, enabling automated speech-to-text workflows with timestamps and diarization.

Core Features & Use Cases

Real-time streaming transcription with asynchronous results and event handling.
Batch transcription of audio files with optional diarization and timestamps.
Seamless integration with Python apps using TranscriptionClient for scalable speech processing across projects.

Quick Start

Install azure-ai-transcription with pip and initialize a TranscriptionClient using your endpoint and key to start real-time or batch transcription.

Frequently Asked Questions about azure-ai-transcription-py

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I perform batch transcription of audio files in Python with diarization and timestamps?▼

Batch transcription of audio files in Python is performed using the TranscriptionClient, which processes large audio archives and outputs text with optional diarization and timestamps. Initialize the client with your Azure endpoint and key to start processing.

How does real-time speech-to-text streaming work in Python applications?▼

Real-time speech-to-text streaming in Python works by using the TranscriptionClient to handle asynchronous results and event handling for live audio. It enables scenarios like live meeting transcription by continuously converting streaming audio input to text.

Do I need an Azure endpoint and key to use the TranscriptionClient for speech-to-text?▼

Yes, you need an active Azure endpoint and key to authenticate the TranscriptionClient for speech-to-text. You must also install the azure-ai-transcription package via pip before setting up the client to access batch and streaming transcription features.

What is the difference between real-time streaming and batch transcription for Python speech processing?▼

Real-time streaming transcription handles live audio with asynchronous event handling, while batch transcription processes pre-recorded audio files. Both methods use the TranscriptionClient to convert speech to text, but batch transcription targets large audio archives rather than live meetings.

Can I process large audio archives with diarization using Python?▼

Yes, you can process large audio archives with diarization using Python by utilizing the batch transcription capabilities of the TranscriptionClient. This identifies different speakers in the audio and provides timestamps for scalable speech processing across projects.