Contact person: Azure Batch Transcription Platform

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Location: Tokyo, United States

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I need an Azure-based solution that takes meeting recordings in MP3, WAV, or M4A, stores them in Blob Storage, and triggers batch processing through Azure Speech-to-Text with speaker identification turned on. After the raw transcript is ready, a second stage (Functions or Logic App) should distill it into clean text that includes the full transcript, concise bullet points, meeting minutes, and clearly marked action items.

At this phase I only need the download to be a plain .txt file; PDF or Word will come later, so design the pipeline with that future switch in mind. Real-time streaming isn’t required—everything can run as asynchronous jobs with status callbacks or a polling endpoint.

Please build and deploy the core workflow, wire up all necessary Azure resources, and hand over:
• Source code with clear README
• Infrastructure templates (ARM/Bicep or Terraform)
• A short walkthrough showing how to upload, monitor, and retrieve the final text file

If you have experience with Azure Speech, Functions, and summarisation (OpenAI/GPT or similar), this should be straightforward. Let me know how you’d structure the components and any third-party libraries you’d lean on." (client-provided description)