Learn how to use Amazon Transcribe and a Python CLI app to extract meeting transcripts, enabling seamless collaboration and brainstorming with GenAI tools.

Amazon Transcribe Pricing

Unlocking Meeting Insights with Amazon Transcribe

Keeping track of critical decisions, action items, and brainstorming outcomes can be overwhelming—especially when meetings pile up and you are not native English speaker lol. Amazon Transcribe simplifies this process for me by converting my audio recordings into searchable, shareable text. In this article, we are going to explore how Amazon Transcribe works and how to automate the workflow using a Python CLI tool.

So… What is Amazon Transcribe?

Amazon Transcribe is a fully managed Automatic Speech Recognition (ASR) service that transcribes spoken audio into text which offers the following features:

  • Multi-language support for global teams.
  • Speaker identification to distinguish multiple speakers.
  • Real-time transcription for instant insights.
  • Custom vocabulary for domain-specific terms.

Amazon Transcribe supports popular audio formats such as MP3, WAV, FLAC, and M4A (processed as MP4). To better understand the pricing model and potential costs, please check out the official Amazon Transcribe Pricing page.

Why Extract Meeting Transcripts?

We all human and it is impossible to remember everything. Recorded meetings often contain critical information that can get lost if not documented properly. But can we document everything? No, we can’t. By transcribing these recordings, we can:

  • Capture Key Decisions and Action Points: Ensure accountability by having an exact record of what was agreed upon. (so we can start pointing fingers at each other. ;))
  • Enhance Team Collaboration: Quickly share meeting outcomes with absent members or stakeholders.
  • Leverage Transcripts for Brainstorming: Feed transcripts into GenAI or other productivity tools for advanced insights. Use it as a context for your GenAI chatbot!
  • Maintain a Knowledge Repository: Turn every meeting into a searchable archive for future reference.

Setting Up Amazon Transcribe for Your Needs

To get started, you’ll need:

  1. An AWS Account: Sign up at aws.amazon.com if you haven’t already.
  2. Proper IAM Permissions: Ensure your AWS credentials allow you to access Amazon Transcribe and Amazon S3.
  3. S3 Bucket: Create a bucket to store audio files for transcription.
  4. Audio Recordings in Supported Formats: MP3, WAV, FLAC, or M4A.

Having these components ready? we can start the fun part!

Automating the Workflow with Python

To save time and reduce manual steps, you can use a dedicated Python CLI application.

This is an example CLI app I created for my personal use. You can find the code here.

This app handles:

  • Uploading Audio: Automated upload to an S3 bucket.
  • Initiating Transcription Jobs: Start and monitor transcription jobs on AWS.
  • Saving Transcripts Locally: Retrieve and store final transcripts for easy access.
  • Error Handling: Simplifies troubleshooting by indicating failed or incomplete jobs.

Real-Life Applications of Meeting Transcripts

  1. Brainstorming with GenAI Feed transcripts into genAI tools for further insights and solutionings.

  2. Creating Summaries for Absent Team Members Keep everyone in the loop by distributing key insights and decisions. No one left behind!

  3. Archiving Decisions for Compliance Many industries require documented evidence of discussions and decisions. Transcripts make compliance like a breeze.

Wrapping it up 👏

Whether you like it or not, we have to join meetings and how to manage the meetings efficiently is another story. But given the fact that we have to join meetings, why not make it efficient and useful? The one of the most efficient way is to transcribe the meetings and use the transcripts for further insights. The information we can get from the transcripts is endless especially when we use genAI tools. Start playing with transcripts! You can thank me later. :)

Cheers! 🍺