快速判断
Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.
适合任务
- 把重复任务整理成可复用的 AI 操作流程。
- 让 AI 在特定场景下按统一规范执行。
- 为团队或个人工作流提供可复制的任务说明。
输入与输出
输入:任务目标、上下文材料、文件路径、约束条件或需要处理的内容。
输出:按 Skill 说明生成的文档、代码、检查结果、计划、建议或操作步骤。
示例任务
- 使用 azure-ai-transcription-py 帮我处理当前任务,并说明执行前需要确认的输入。
- 根据 azure-ai-transcription-py 的说明,给我一个安全的使用步骤清单。
安装方式
- 下载本站提供的 Skill ZIP 并解压。
- 把解压后的 Skill 目录放入当前 AI 工具支持的
skills目录。 - 如需在线查看原始内容,可打开 GitHub 的
SKILL.md。
风险边界
使用前请检查权限、外部依赖和要处理的数据类型。不要把密码、密钥、身份信息或敏感客户资料交给未经确认的 Skill。
SKILL.md 文档介绍
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-transcriptionEnvironment 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
When to Use
This skill is applicable to execute the workflow or actions described in the overview.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.