fast-transcription

Transcribe contact center audio with speaker identification via Azure Speech.

Updated Jan 15, 2026
One-click install
npx skills add https://github.com/samelhousseini/microhacks --skill fast-transcription
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fast-transcription
Source: https://github.com/samelhousseini/microhacks/tree/main/.github/skills/fast-transcription
Command: npx skills add https://github.com/samelhousseini/microhacks --skill fast-transcription

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, python-dotenv, pydub, and includes scripts (resource) components.

What problem does it solve?

This Skill enables rapid transcription of contact center calls with built-in speaker identification, reducing manual review time by delivering per-channel and diarized transcripts in real time or faster-than-real-time.

Core Features & Use Cases

  • Stereo channel transcription: agent and customer on separate audio channels for accurate speaker labeling.
  • Mono diarization: single-channel recordings with recognized speaker turns and a combined transcript.
  • Quick-start guidance for deploying Azure Speech Fast Transcription with minimal setup and secure credential handling.

Quick Start

  • Install dependencies from requirements.txt, set AZURE_AI_SPEECH_ENDPOINT and AZURE_AI_SPEECH_KEY in your environment.
  • Use the Python API to transcribe with stereo channels or diarization, e.g., a simple call to TranscriptionClient().transcribe_stereo(...) or transcribe_with_diarization(...).
  • Review the output: agent and customer transcripts, combined transcript, and basic analytics.

Frequently Asked Questions about fast-transcription

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

FAQPage Schema
How do I transcribe contact center calls with speaker identification?▼

Contact center call transcription with speaker identification uses stereo channel separation or mono diarization to label speakers automatically. It returns per-channel or per-speaker transcripts along with a combined transcript for faster-than-real-time review.

What's the best way to separate agent and customer audio for transcription?▼

Stereo channel transcription separates agent and customer audio onto distinct channels for accurate speaker labeling. This approach processes both channels simultaneously to deliver faster-than-real-time results.

Does Azure Speech support faster-than-real-time transcription for mono recordings?▼

Azure Speech Fast Transcription supports mono diarization to recognize individual speaker turns on single-channel recordings. It returns a combined transcript with identified speakers at faster-than-real-time speeds using API version 2025-10-15.

Do I need an Azure Speech endpoint to use real-time call transcription?▼

Real-time call transcription requires an Azure Speech endpoint and API key configured in your environment. You set AZURE_AI_SPEECH_ENDPOINT and AZURE_AI_SPEECH_KEY to authenticate transcription requests.

How do I set up Python dependencies for Azure Speech Fast Transcription?▼

Install Python dependencies from requirements.txt including requests, python-dotenv, and pydub. Configure Azure credentials in your environment, then call TranscriptionClient().transcribe_stereo(...) or transcribe_with_diarization(...) to begin.

When should I use stereo channel transcription instead of mono diarization?▼

Use stereo channel transcription when agent and customer audio are recorded on separate channels for precise speaker labeling. Mono diarization is better for single-channel recordings where speaker turns must be identified algorithmically.