From antigravity-awesome-skills
Transcribes speech to text using Azure AI Python SDK for real-time streaming and batch processing with speaker diarization and timestamps. Use for audio transcription tasks.
npx claudepluginhub sickn33/antigravity-awesome-skillsThis skill uses the workspace's default tool permissions.
Client library for Azure AI Transcription (speech-to-text) with real-time and batch transcription.
Transcribes speech to text using Azure AI Python SDK for real-time streaming and batch processing with speaker diarization and timestamps. Use for audio transcription tasks.
Implements Azure AI Transcription SDK in Python for batch and real-time speech-to-text with diarization, timestamps, and multi-speaker support.
Transcribes audio files to text using OpenAI APIs with optional speaker diarization and known-speaker hints via Python CLI. Useful for extracting speech from recordings or labeling speakers in meetings.
Share bugs, ideas, or general feedback.
Client library for Azure AI Transcription (speech-to-text) with real-time and batch transcription.
pip install azure-ai-transcription
TRANSCRIPTION_ENDPOINT=https://<resource>.cognitiveservices.azure.com
TRANSCRIPTION_KEY=<your-key>
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"]
)
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)
stream = client.begin_stream_transcription(locale="en-US")
stream.send_audio_file("audio.wav")
for event in stream:
print(event.text)
This skill is applicable to execute the workflow or actions described in the overview.