I see what you speak. NLP and Speech-to-Text (part one)
We don’t like clickbait titles in general. And, although this one might sound like one, it isn’t. This article will look at the NLP (standing for natural language processing, not neuro-linguistic programming) and the technologies and importance of the market research industry.
NLP is the machine’s ability to process natural language inputs. Some major industry verticals are already pushing the boundaries of the available machine learning options and open APIs:
- Healthcare – uses NLP to understand patient conditions and process medical records and prescriptions and early disease detection.
- Psychology – the NLP is gaining traction in finding behavioral patterns in patients and, an example – preventing suicide.
- Legal – there is a hype around the ability of NLP, combined with additional ML algorithms, to understand and even write legal documentation based on user input that is not legally bound.
- Insurance – NLP is used to process user documentation and analyze behavioral patterns.
NLP research and development is an ongoing battle between the largest companies like Google, Amazon, Microsoft, and Apple, especially in PA (personal assistance) services. These companies are actively developing PA products like Cortana, Alexa, and Siri. And, yes – for the PA products is crucial to understand and process the user input properly.
But this technology is not limited only to the personal assistance field. Voiceover companies, automation services, and this is the topic that is important for us.
At Bright, we’re using this technology in some of our market research products, and it’s indeed impressive. An example, our Bright AGI gibberish inspector uses it to track and detect gibberish texts in open-end questions. Another fair use is in our Bright TC text-coding tool, where we use NLP to suggest possible coding options for user open-ends.
You might want to check out also the second part of this article, which covers in details another aspect of the NLP – Speech-to-Text.