Week 5 - BALT 4364 - Natural Language Processing

NPL

Natural Language Processing (NLP) is a branch of AI that focuses on understanding how humans communicate—hence the name. NLP is particularly valuable in industries that rely heavily on qualitative analysis. For instance, in my current role in market research, we conduct interviews with foodservice professionals, such as chefs and food scientists, to gather their feedback on various products. Capturing and analyzing all of that information manually is time-consuming and often overwhelming, but NLP significantly streamlines the process.

We use a program called TurboScribe to transcribe each interview within minutes, though there are many similar tools available. One feature we appreciate most about TurboScribe is its ability to identify individual speakers and organize the transcript into clear sections, rather than producing a continuous block of text. It also allows us to click on any part of the transcript and hear the corresponding audio, perfectly synced, which makes verifying accuracy much easier before we move on to sentiment analysis.

That said, NLP tools aren’t flawless. For example, brand names can sometimes trip up the AI, requiring manual edits to ensure accuracy. While that’s a minor inconvenience, it’s something to keep in mind. In market research, sentiment analysis is one of the most critical parts of our work, so accuracy is essential. There's also a major efficiency gain—NLP doesn't replace the human element, but it does dramatically reduce the time and effort required to analyze interviews.

Ultimately, it’s about finding the tools that improve workflow and boost productivity—because, as the saying goes, time is money. What excites me most is that all of this is possible with tools powered by Python. In the coming weeks, I’ll be diving deeper into NLP to develop custom solutions tailored specifically to our company’s needs. Stay tuned!