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Azure Ai Transcription Py

核心功能:支持实时及批量语音转文本,可开启说话人分离、生成时间戳,提升识别精度。典型场景:多说话人会议转录、视频字幕生成、实时语音内容识别。输入支持本地音频文件、音频流、云存储音频URL;输出含转录文本、说话人标识等元数据。需配置Azure认知服务端点与密钥,通过Python代码调用,有清晰的使用示例。

thegovind
thegovind
热度 97.03
最近更新 2026-05-11 15:51:31
分类:开发依赖:代码执行 / 第三方 API应用场景:代码生成 / API 集成 / 文件转换

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add azure-ai-transcription-py
Metadata
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

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

  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