What is NLP(Natural Language Processing)?

Which is the most powerful tool that picks up human beings to the top of the pyramid? Which is that big advantage that makes us the leading species on Earth? Our power is our language. Our most complicated component. The ability to give and exchange information and ideas.
Talking about computers in this sense, it is meaningful to mention that nowadays we are experiencing the transition from those rule-based computer systems to AI-based ones. Systems that are able to understand natural language which is more complicated than those simple rules of syntax. And the most challenging thing is that we are within a stone’s throw to get there.
The present article reveals the technology of language processing by computers, abbreviated as NLP. NLP stands for Natural Language Processing, which is a subfield of AI (Artificial Intelligence) where computers are able to comprehend the human language and communicate through its instrumentality. It represents a part of computer science and AI which deals with human languages and helps computers to understand them.
However, to understand a spoken language is a quite difficult task. If you are not a human being, such specific aspects like words with several different meanings, different speakers with different accents, a large variety of vocabulary will be incomprehensible. Of course, it is impossible to help computers in understanding natural languages by giving them a general dictionary of all potential sentences. The key is to teach them some grammar rules. Using those pieces of knowledge of sentence structure, machine learning pattern recognition, idioms, and other aspects — it becomes possible.
The truth is that NLP is already used on a large scale in our everyday life, as an indispensable part of our everyday activity. Here are some meaningful examples of NLP use cases.
The first one, and one of the most important is sentiment analysis. Sentiment analysis represents an automated process of comprehending an attitude about a given issue from written or spoken language. Nowadays our world generates a huge amount of information every day, and in this sense sentiment analysis has become a key tool for making sense of that data.
The second, and the most interesting use case for us is the implementation of chatbots. The process of interaction with a chatbot becomes possible due to the NLP technology. Here we are talking about speech recognition. The most prominent examples in this sense are the well-known Siri, Cortana, and Google Assistant.
Machine translation. Here NLP is used to translate a piece of certain information from one language into another. The convenience of such a technology consists in the fact that you can do it effortlessly, in real-time.
The use of NLP is assuredly amazing. It is outlandish, but at the same time, it seems to be an unobserved, colossal help for people. It is incredible how the NLP technology, which represents a complicated process at a high degree, is able to simplify our daily tasks when we need for instance a keyword searching, spell checking or information extraction from a big amount of data. Also, Natural Language Processing has such a great application as Advertisement Matching. This means that the suggested advertisements will reflect your real history of searches, that is to say, by the medium of NLP technology you will see only advertisements of the belongings that you are really interested in.
In order to understand, to the greatest extent, what is NLP and how this technology works, it is important to consider the two major components of NLP. First comes the natural language understanding. Natural language understanding, called (NLU) or that is to say natural language interpretation (NLI). It represents a concept which derives from natural language processing (NLP) in artificial intelligence (AI) that makes mention of machine reading comprehension. After that, comes the natural language generation. Natural language generation (NLG) presents the image of a software process that converts logical information into another clear idea. It is interesting that, as in the case of a chatbot, it can produce brief and precise announcements of text in mutual dialogue which a text-to-speech system might even read out loud. As a rule, the natural language understanding represents a more complicated process than that of natural language generation. It is one of the most common challenges in natural language processing, going hand in hand with speech recognition and of course natural language generation. That is because of the fact that for a machine it takes a lot of time and a lot of steps in order to understand a certain language. That is why (NLU) is considered to be an AI-hard problem.
In order to make a brief conclusion of the above we can remind that NLP represents a field which is contained in such fields like computer science, and artificial intelligence involved in the intercommunications between human (natural) languages and data processing machines, especially how to program computers to handle and evaluate large amounts of natural language info.