How to build a Chatbot with Natural Language Processing

How to Use NLP for Building a Chatbot

Imagine if part of your work was performed by a computer. Like, some intelligent computer may work as information on your website or answer customer calls… Fascinating, isn’t it? But it is no longer sci-fi, it’s a reality now: the modern chatbots are no longer differ from a human.

See how natural language processing (NLP) can greatly facilitate our everyday life in our new blog post.

Let’s start with the basics: what is Natural Language Processing

What is Natural Language Processing is used for? NLP is a branch of informatics, mathematical linguistics, machine learning, and artificial intelligence. NLP helps your chatbot to analyze the human language and generate the text.

Use of Natural Language Processing includes the following aspects:

  • Natural language understanding

Our language is a highly unstructured phenomenon with flexible rules. If we want the computer algorithms to understand these data, we should convert the human language into a logical form.

  • Natural language generation

With the help of natural language understanding (NLU) and natural language generation (NLG), it is possible to fully automate such processes as generating financial reports or analyzing statistics.

  • Natural language interaction

After the previous steps, the machine can interact with people using their language. All we need is to input the data in our language, and the computer’s response will be clear.

What is chatbot?

A chatbot is a computer program or artificial intelligence that communicates with a customer via textual or sound methods. Such programs are often designed to support clients on the websites or via phone.

The chatbots are generally used in messaging applications like Slack, Facebook Messenger or Telegram. They can order your food, buy tickets, or show the weather podcasts.

How chatbot works: scripts and artificial intelligence

Despite the number of programs and natural language processing tools, the chatbots can be divided into two types:

  • Scripted chatbots. When encountering a task that has not been written in its code, the bot will not be able to perform it.
  • Artificially Intelligent chatbots are based on NLP. They react to the meaning of the whole question. The AI-based chatbot can learn from every interaction and expand their knowledge.

Challenges for your Chatbot

Imagine if you were a computer: would it be easy for you to understand natural speech? Despite its structure, the human language is chaotic. Therefore, how does natural language processing work? We have a lot of elements in our speech that affect the understanding of a chatbot and may become challenges in natural language processing:

  • Synonyms, homonyms, slang
  • Misspellings
  • Abbreviations
  • Omitting punctuation rules
  • Different accents

People can understand the meaning of context, intonation, body language, experience. We can understand how a chatbot works: as far as the machine does not have this linguistic experience, NLP implies teaching the computer to understand the speech despite the distractors.

Where you can use your chatbot?

The bots can provide phone or chat support answering the simple questions. Meanwhile, the complicated tasks pass to a human operator. Here are examples of chatbot use cases:

  • Customer service chatbot

The chatbots can provide clients with information about any company’s services, help to navigate the website, order goods or services (Twyla, Botsify, Morph.ai).

  • Medicine

Natural language processing chatbot can help in booking an appointment and specifying the price of the medicine (Babylon Health, Your.Md, Ada Health).

  • Tourism

The program can inform you about the ticket prices, places of interest, restaurants, souvenir shops, etc. (Skyscanner, Cheapflights Chat, Roomfilia).

How to implement a machine learning chatbot

You will definitely go through the following stages:

  • Business logic analysis

This step is required so the developers’ team can understand our client’s needs.

  • Channel and technology stack

If the client wants to create a voice chatbot, it is better to use the Twilio platform as a base channel; in case of text chatbots the Telegram, Viber, or Hangouts will suit better.

  • Development

The creation of the machine learning chatbot consists of two steps: the development of client-side bot and connecting it to the provider’s API (Telegram, Viber, Twilio, etc.).

  • NLP integration

Once we are done with the development, we can connect artificial intelligence.

  • Testing

Once the bot is ready, we start asking the questions that we taught it to answer. As usual, there are not many scenarios to be checked so we can use manual testing.

Artificial intelligence chatbot can attract more users, save your time and raise the status of your site. Therefore, the more users are attracted to your website, the more profit you will get.

In Sloboda studio, we can provide you with full assistance with your first smart bot. Using the characteristics of the client’s speech (words frequency, vocabulary, slang), we can change the chatbot’s communication style by turning the so-called mirroring effect. This method helps to increase the trust of customers and the sales for our clients and make use of natural language processing available for customers.

Serhii Znakhur

Serhii Znakhur

AI Developer, Data Science Expert, Project Manager

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