Pragmatic Analysis: The Last Frontier of NLP

Trinity: No one has ever done anything like this.. .Neo: That’s why it is going to work.

The Matrix

Fact I: Babies learn to communicate before learning to speak.

Fact II: if you google the term “Pragmatics” (the meanings and intentions at the base of our communication) you’ll find it to be categorized as a “sub-field” of linguistics.

This, imho, is the source of all evil in NLP today.

Teaser: for those who proclaim to provide “insights” or “tips” on communication between people through the analysis of the words and phrases used, I can also say: “good luck, morons”.

It all goes back to the nerdy, socially detached, hallucinative assumption that language is “objective” and can be understood without multiple layers of context. Sure, some very short utterances such as “this dog is eating” can be seen as objective, but communication between two humans or more, almost never is.

Words don’t Kill. They are just the messenger

Words don’t kill. Vicious acts of social humiliation executed via words can kill. You can also humiliate a person with touch (haptic communication): just think about this visual: President Trump gives Barack Obama a joyful “good-dog” pat on the head. Or through Kinesics (body language): think of Obama looks to the left while raising his eyebrows while Trump makes an argument.

This examples are very easy to understand, because they are our real, primary, first language. As babies, we learned to make sense of Proxemics, Kinesics, Haptics and Paralanguage before learning to construct our first sentence. And to this day, when you listen to someone talking in English (given that English is your first spoken language) – you make an unaware interpretation to your primary first language – your baby language – which we’ll call Pragmatics.


Social status perceptions, emotions and sentiments play a critical role in our daily lives, aiding decision making, negotiations, communication, learning, etc. Over the past decades, researchers in artificial intelligence have been trying to program machines to express a variety of social and emotional utterances at the right time and context, so far with limited success, but improvement is incremental and consistent.

All these efforts can be attributed to affective computing, an interdisciplinary field spanning computer science (ML, NLP, Deep Learning), psychology, social sciences and cognitive science.

To be continued

Acknowledgements: Paulo Malvar, Max Ved, Devamanyu Hazarika, Soujanya Poria, Eric Cambria, Amir Hussain. T

SubStrata's SCIP extract pragmatic meanings from text, audio and video in transactional interactions
SubStrata SCIP extract pragmatic meanings from text, audio and video in transactional interactions

Tech Entrepreneur, co-founder of SubStrata Technologies

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