Aug 18, 2020

Motivating Natural Language Processing Part 2: The Most Productive Meeting You Never Attended

Matthew Roberts

Matthew Roberts

Motivating Natural Language Processing Part 2: The Most Productive Meeting You Never Attended

Everyone dreads the classic business meeting, and it’s long overdue for a modernization. Natural language processing (NLP) is a powerful set of tools that can transform the way companies do business. NLP concepts such as document tagging, summarization, named entity, and intent recognition could change the way meetings work—so they actually work.

This is the second part of a series designed to shine a light on NLP. In the first part of this series, we introduced some key terminology and provided some innovative improvements to the standard chatbot use case. In this blog post, we’ll look at how NLP can make meetings more productive.

The Reality

Picture the last meeting you attended. Maybe, like me, you spent half of the meeting furiously taking notes, trying to summarize key decisions or capture action items for both you and your colleagues. Afterward you circulated a series of hopeful emails to your teammates, praying their notes could fill the gaps you find in your own. Worse yet, maybe it's been several weeks and you can't find those notes amid the clutter of your notepads, half the action items have gone unfulfilled, and finally, you concede—it's probably best to just meet again for round two.

Does that sound familiar?

The Future

Now picture that same meeting. You engage your colleagues in productive conversation. Decisions are made quickly and effectively. No notes are taken. It ends early.

Afterward, the recorded audio is transcribed and emailed to all attendees. Names of people and companies, technical language and jargon are all captured with incredible accuracy. Better still, this transcript is summarized in the body of the email, providing a holistic overview for those unable to attend. To top it all off, these notes and summary are uploaded to a shared drive where they are automatically tagged with key people, terms, or topics of discussion, and where they can easily be found months later with a simple search.

Does that sound better?

NLP Tools Can Transform the Way You Run Your Business

This doesn't have to be some farfetched pipe dream. Robust and rapidly improving natural language toolsets can make this dream a reality today.

Speech-to-text applications save the note taking for the computers, allowing you to focus on the task at hand. Powerful machine learning algorithms tuned to your business capture all your domain-specific terminology with ever-increasing accuracy.


Audio input is processed by standard English language models combined with domain-specific models to capture contextual phrases and transform it into a textual transcript.

Document summarization tools capture broad themes from the discussion to share with a wider audience, while named entity and intent recognition extracts key decisions and action items from the lengthy transcript to highlight the most important details.


Textual transcripts are parsed to extract key information—broadly topical phrases for summarization and specific intents for action item identification.

Document tagging algorithms take charge when your notes are uploaded to the cloud. Key words and topics are automatically associated with your transcript, linking these notes to notes from similar meetings and ensuring easy discoverability months down the line.


The content of each transcript is compared against the content of existing, pre-tagged documents. Similar features are identified to determine which of the available tags are most appropriate for this document.

Time to Organize Your Documents

Does your business deal with documents in need of organization and analysis? NLP tools could help automate and enhance these processes. We’d love to help! Get in touch with us at to learn more.

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