Use Azure's Python transcription client to turn audio files into text and review timestamped results. Covers authentication, installed SDK options, and error handling, while clarifying when streaming or asynchronous batch work needs a different Speech API.
Azure AI Transcription SDK for Python. Use for audio-file transcription with timestamps; distinguish this client from streaming and asynchronous batch Speech APIs.
Run score Not tested
See how to installThis skill helps implement audio file transcription in Python with Azure's azure-ai-transcription. It covers passing a file to TranscriptionClient, specifying a language, and reviewing results with timestamps. It also explains key-based authentication and when DefaultAzureCredential can be used, along with explicit handling for empty results and service errors.
Use it to transcribe a local recording with consent or to check which settings are supported by the installed SDK. It can also help clarify how file transcription differs from streaming audio and asynchronous batch processing, which use different Speech APIs.
Pin the SDK version in an isolated Python environment. Before uploading, check the Speech resource, endpoint, permissions, consent, cost, and retention. Keys, audio contents, and full transcripts are not logged by default. Use a different Speech API for streaming or asynchronous batch processing. The examples have not been tested against Azure; verify availability, accuracy, and cost in the authorized environment.
This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.
AI checked the SKILL.md for operations that need care and for setup requirements. The score comes only from actually running the skill (hands-on test).
Not counted in the score. Rated by AI (OpenAI Codex) as of Oct 24, 2026. Treat it as a guide and read the original before installing.
Review the instructions the agent will receive before you install.
azure-ai-transcription client.Use a project-pinned SDK in an isolated Python environment. Confirm the Speech resource, endpoint, permissions, audio consent, cost and retention before upload. Do not log keys, audio contents, or full transcripts by default.
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.transcription import TranscriptionClient
from azure.ai.transcription.models import TranscriptionContent, TranscriptionOptions
client = TranscriptionClient(
endpoint=os.environ["TRANSCRIPTION_ENDPOINT"],
credential=AzureKeyCredential(os.environ["TRANSCRIPTION_KEY"]),
)
with client:
with open("audio.wav", "rb") as audio:
result = client.transcribe(TranscriptionContent(
definition=TranscriptionOptions(locales=["en-US"]), audio=audio,
))
# Inspect result locally; handle empty output and service errors explicitly.
DefaultAzureCredential is also supported when the identity has the required
resource role. The previous begin_transcription and begin_stream_transcription
examples did not match this client. Do not invent a streaming adapter.
“Transcribe this consented local recording; keep the transcript private.”
Verify installed signatures and service limits against Microsoft's SDK guide. This illustration has not contacted Azure; availability, accuracy and costs require verification in the authorized environment.
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