How to Use NLP for Building a Chatbot

How to Use NLP for Building a Chatbot


In the age of computer technologies, artificial intelligence progresses rapidly. Some years ago smart houses and self-driving cars were just ideas for sci-fi novels and movies – nowadays they are a reality. Some years ago scientists all over the world were disputing whether it was possible to create a computer with human intelligence. Nowadays, specialists in such branches of computer science as machine learning and natural language processing (NLP) are actively capable of doing this.

NLP is an area of study at the intersection of artificial intelligence and mathematical linguistics. It aims to enable computers to understand, analyze and use human language so that we can have a conversation with machines using natural languages like English instead of digital ones.

Although training a machine to use human language appears to be rather a challenging idea, it has great potential in the further development of computer sciences. In this article, we will tell you about NLP chatbot development and how the bots can greatly facilitate our everyday life.


What is NLP

Natural Language Processing is one of the steps of a large mission of the technology world – to use artificial intelligence to simplify the everyday life of the modern world. Machine learning and deep learning have already achieved impressive results in this area and the specialists in these areas are constantly opening our eyes to new possibilities.

Machine learning is widely used to process and structure huge amounts of data. It can also be used for programming chatbots capable of automating the sphere of customer support. Deep learning is used for teaching the machine to imitate the work of human brains. However, the machines’ imitation of human activity is impossible without their ability to work with the human language – the main thing that distinguishes the human from other living and artificial creatures.



How NLP works

One of the main principles of working with NLP is splitting the complex language system to atomic ones and teaching the machine to interact with them. The ability of the computer to deal with the human language consists of the following aspects:

  • Natural language understanding

The main part of the machine’s interaction with a human language is the ability to understand it. A language is a highly unstructured phenomenon managed by flexible rules (not to mention abbreviations, slang, misspellings, and accents). Different emotions and meaning are put into the text. In order for the machine to work and understand such data, the human language should be converted into a logical form understandable to the computer algorithms.

  • Natural language generation

Having the data structured and analyzing their meaning, the machine is to turn it into a written narrative by generating readable text. With the help of NLU and NLG, it is possible to fully automate data-driven narratives by generating financial reports, analyzing statistics, etc.

  • Natural language interaction

Natural language interaction is the result of the aforementioned stages: having the skill of analyzing human speech and generating a human-like text, the machine is able to interact with people in their own language. In order to be understood by a computer, we no longer need to give them commands using programming algorithms – it is sufficient just to input the data in our language. In its turn, the computer will give the response in the same way that is understandable for us.


Tools and methods used in NLP

The machine perceives the text as a mere sequence of characters. In order to fully process the text by understanding the meaning, the computer needs to split it into minor units and analyze the connections between them. This is a rather complex process consisting of several stages of understanding. We will tell you about the first stage that is commonly called basic processing and includes the following techniques:

  • Parsing – syntactic analysis of the text: identifying the sentences and their meaning.
  • Tokenization – the text is divided into tokens (meaningful units that can be words, phrases, or sentences) that are used for the further analysis.
  • Lemmatization/stemming – reducing the inflectional form of the word to the root. The difference between them is in the complexity of the algorithms: while stemming just cuts off all the inflections, lemmatization takes into account the morphological structure of the word and leaves the basic form. Let’s see the difference between the two methods using the example words “study,” “studies,” and “studying.”


Word Inflection Stem Morphological information Lemma
study -y stud Infinitive of the verb “study” study
studies -ies stud Third person, singular, Present Simple of the verb “study” study
studying -ing stud Gerund of the verb “study” study


  • Language detection – detects the human language of the entire document or of every single sentence.
  • Part-of-speech tagging – the process of recognizing the part of speech and the grammatical form of the word by using the rules coded in the computer. Once this process is completed, the computer probably understands the meaning of the text.


The challenges of working with NLP

Despite its complexity, the human language is a highly unstructured system of synonyms, homonyms, terms, and slang, not to mention possible misspellings, contracted forms, abbreviations, and omitting punctuation rules. In oral speech, we have different accents, mumble, and mispronounce the words. For the human, it’s easy to understand the meaning of the word from the context and life experience, by intonation or by the body language of a partner – we do this automatically, without paying attention to the way we perceive the speech of another human. The machine does not have this linguistic experience, and NLP implies teaching it to understand the meaning of the speech despite the aforementioned distractors.



How NLP can be used in everyday life

NLP helps to simplify people’s everyday interactions with computers. Having been taught to deal with the human language, the computer is capable of reading text and understanding the content and sentiment and determining its most important parts. Teaching the computers to process the texts will automate and accelerate the following actions:

  • Processing huge volumes of text data

A machine can do routine and complex work with texts without tiring and with higher efficiency than humans. With the help of NLP, it’s possible to analyze the text and generate a brief summary or to extract relevant data. This can be widely used for processing and structuring the financial, legal, and technical documentation with a large amount of statistics or technical information.

  • Machine translation

NLP-based software is able to translate the selected text to a different language within seconds. The translation highly depends on the context and regional varieties of the language. In order to make an accurate rendering, the machine must not only perceive every separate word but analyze the meaning of the sentence, paragraph, and the content and sentiment of the total text.

Fiction texts are difficult for machine translation – they highly depend on the author’s style, which will be confusing for the computer. However, technical information, scientific information, and other types of texts where preciseness is of primary importance can be rendered by a computer rather accurately.

  • Business

NLP can be used for creating intelligent chatbots that communicate with the customers and help them to make purchases or fix some minor issues. The intelligent bots are able to correctly interpret colloquial speech, misspelling, and the omission of punctuation in order to provide the relevant answer to the client’s inquiry. Some of them are able to copy the client’s style of speech making the bot-generated texts sound more human.


What is a chatbot?

A chatbot is an AI-based program designed for direct interaction with a human using natural language. The users use the chatbot via a graphical interface for written or oral form. The chatbots are generally used in messaging applications like Slack or Telegram, and can perform different actions, such as ordering food, buying railway and aviation tickets, managing your finances, showing the weather anywhere in the world, etc.



How chatbots work: scripts and AI

A chatbot is not a new type of software. The first was developed in the ’60s. It was named ELIZA and it simulated a psychotherapist’s dialogue with a patient by rephrasing the human’s words to the questions and reacting to the keywords. For example, if the user’s answer contained the word “husband,” “wife,” “son,” “daughter,” “mother,” “father,” etc., ELIZA would probably ask them to talk about their family.

The research demonstrated that users are interested in communication with intelligent programs and new chatbots started appearing rapidly. Each new one has become even smarter than its predecessor and is able to perform new sets of actions. Despite the amount of the programs and their functions, the chatbots can be divided into two types:

  • Scripted – they are programmed with a set of scripts that enable them to perform a certain number of actions and to answer certain types of questions. When encountering a task that has not been written in its code, the bot will not be able to perform it.
  • Intelligent – they are based on NLP and are able to understand the meaning of the human language. Unlike the scripted bots, they react not to the certain words or constructions but to the meaning of the whole question. Additionally, the AI-based chatbots can learn from every interaction and expand their knowledge automatically.


Where are they used?

The bots can be a valuable helper in our business and everyday life. They will make booking the services and searching for necessary information fast and simple. Here are examples of chatbot use in different spheres of life:

  • Sales, customer service

The chatbots can automate the sphere of customer service. They can give clients the necessary information about the company’s services, help navigate the website, and order goods or services. Additionally, a chatbot can provide phone support: the program is able to give the clients all the necessary information, and to perform simple actions. Only the complicated tasks will be passed to a human operator.

  • Medicine

A program will never substitute for the work of a human doctor. However, it can help to book an appointment with the necessary specialist and to tell you where and for what price you can buy the necessary medicine.

  • Tourism

With the help of a bot you can easily buy tickets to different destinations and book rooms at the hotel. The program can tell you the prices of the entrance tickets, interesting places to visit, where to eat, to buy souvenirs, etc.



The development of artificial intelligence implies extending the possible areas where Natural Language Processing can be applied. Although teaching a machine to deal with human language is a rather difficult and long process, we can be sure that the linguistic skills of computers will continue to improve.

In this article, we have told you about the general principles of using Natural Language Processing for chatbot development. However, our expertise in this area is not limited to this information – we are going to present you another article with practical information on how to build a chatbot. Stay tuned, and feel free to contact us with any questions!

Serhii Znakhur

Serhii Znakhur

AI Developer, Data Science Expert, Project Manager
  • Ajit Sharma

    How can I use NLP to extract the intent of the text, I guess this will be crucial to produce the response.

Join our Newsletter