What is NLP?

Natural Language Processing (NLP) is one of the most important components of Artificial Intelligence (AI). Companies across the world are investing more and more in NLP solutions, why? Because there is strong business potential. According to my understanding; as of 2020 every business/ company is a software company because a business needs an advantage edge in technology to remain standing. And soon, every business will be incorporating AI in their core business models.

NLP helps machines read text by simulating the human's ability of language understanding.

Applications of NLP

Applications of NLP are highly increasing and covering more industries,

i.e.

  • Search engines
  • Chatbots
  • Speech recognition
  • Intent Classification

NLP is everywhere even if you don't realize it. Does your word software auto-correct you? that's NLP in action. 

Conversational AI

NLP is the umbrella of conversational AI; you can create a virtual assistant that can chat and detect user's intentions with it. In an era where real-time matters, virtual assistants are a perfect solution. They'll convert prospects into customers when they have a problem, preventing them from switching to a competitor by quickly finding a solution and answering their questions.

For Conversational AI systems to talk back or write back, they have to use Natural Language Generation (NLG), which enables a computer to write something humans can understand.

Sentiment Analysis

With the help of certain machine learning algorithms, sentiment analysis helps in estimating customer feedback of brand and product reviews while adjusting sales and marketing strategies. Today NLP can detect text emotions like; happy, sad, confidence, etc which can be very useful for a business that is trying to understand the clients' views of their products. It can also be used to detect abusively or hate speeches in chat groups, or a room through speech recognition.

Speech Recognition

Speech recognition helps transform voice commands to text and vice versa, all modern Conversational AI systems utilize speech recognition. Many businesses use CCTVs and some employ computer vision to detect certain objects or actions, others with audio input CCTVs employ speech recognition and sentiment analysis to fully understand and capture every bit of information in their stores.

Question-answering

Today many businesses have lots of data, documentation, readme documents, knowledge base, and lots of information about them and their products and services. Customers don't really have to read all the information sometimes they just have a question. And the speed at which that question is answered determines if they will buy from you or not. Most businesses today have way too much data that even a human employee will have to research and study the documentation first before responding to the client.

With the question-answering (QnA) system, a business can compile all its data into a model that can be used to provide answers about all it offers instantly. A business can even enable its virtual assistant to access its QnA as a skill to be a great customer support agent.

Document Summarization

Information overload is a real problem, sometimes all we need is a specific, important piece of information from a huge knowledge base. Summarization does not just maintain the meaning of the document but also maintains the emotional meaning of the document. 

Summarization can be used in collecting segments from blog posts, social media, and most advanced virtual assistants employ this when searching the web for answers.


As the amount of information available online is growing, we discover that most of it is unstructured and we need NLP to help us structure the data and making useful and accessible by everyone, Google is good at this and you also need NLP to boost your sales and understand your clients and employees better.