How NLP changed the abilities of chatbots

Chatbot is a great way to make Internet communication more enjoyable for both customers and businesses. At the beginning of the millennium, people would probably laugh at you for this phrase. But not today. The main reason for this change is Natural Language Processing (NLP). It is this branch of artificial intelligence that has transformed clumsy and awkward automatons into today’s intelligent chatbots that can hardly ever be told from humans.

Thanks to NLP, artificial intelligence learns to understand something as complex as human communication. The natural speech that people use to talk to each other is completely different from the abbreviations, phrases, and slogans spoken by the first chatbots. Thanks to NLP, artificial intelligence is finally beginning to understand its creators.

A lot happens behind the chat window with the chatbot (source: unsplashl.com)

The acronym NLP covers knowledge of the development of artificial intelligence, linguistics, mathematics and machine learning. All of this is needed for artificial intelligence to be able to accept, either in the form of voice or text, a natural human message, understand it, and be able to respond to it correctly. Thanks to NLP, people’s language shifts from entering slogans and weird phrases into a full-fledged conversation when communicating with chatbots.

Knowledge of NLP allows chatbots to do more than what programmers directly put into them. Chatbot without NLP cannot exit programmed songs, and any speech that deviates from them will not be processed. The solution simply doesn’t understand it – and the author has no choice but to communicate with the slogans the chatbot needs. Consequently, all the naturalness or pleasure of communication disappears. And with that, for example, the desire to shop where this chatbot is an obstacle.

NLP frees chat bots (and voice bots) from these songs and detaches them from the shackles of preset patterns and slogans. NLP chatbots not only understand the meaning of words, but also understand whole sentences or even the context and intentions of the person on the other side of the conversation.

Chatbot is nothing without proper training (source: unsplash, com)

NLP not only makes life easier for those with whom you can chat. It also helps programmers. If you want to learn chatbot without NLP, answer the question: How much do I pay for this price per month? You have to teach him word for word a variation of each question or rely on preset buttons. However, with NLP, the customer does not have to hit the exact phrase that the chatbot knows. The solution understands everything from context and ultimately asks for the missing information itself.

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Chatbot’s ability to learn and develop independently is one of the greatest merits of NLP. The work of developers has changed from the slavish entry of words and phrases into the training of true artificial intelligence. And over time, the chatbots started learning for themselves. Not only during their creation, but also during use. Each new conversation brings them new insights to better understand common expressions and connections in interpersonal communication. Chatbot is gradually improving as if a human operator were in place.

In addition, a virtual assistant equipped with NLP is not surprised by the shortcomings in written human communication. With its knowledge and ability to work in context, it is able to handle spelling and grammatical errors, while one client’s typo eliminates its predecessor from the game.

NLP allows a chatbot not to understand our words with just a bunch of letters (source: unsplash.com)

But even a chat bot with NLP features can’t discuss all the latest fashion trends in nuclear physics. But it can talk smoothly in the area of ​​specialization of the company that developed the solution. So if you meet it on the website of a mobile operator, for example, it can solve with you the same things that its human colleagues could do in the same place. But don’t ask it, as well as its fellow human beings, for advice on what to wear this summer.

But what does the thought process of the NLP chatbot that just received your message look like? The route to the answer consists of five steps, which ideally take place in a series of flashes – tokenization, normalization, entity recognition, dependency parsing, and creation.

Step 1 – Tokenization: Chatbot divides the message into small pieces of information

Step 2 – Normalization: Chatbot corrects errors, typos, and slang expressions

Step 3 – Identifying Entities: Chatbot determines where the words refer. Watermelon is defined as the fruit, Mount Everest as the mountain and 55 as the number.

Step 4 – Parsing the Dependency: Chatbot divides words into nouns, verbs, sentences, and other grammatical units

Step 5 – Generation: Chatbot creates possible answers and selects the most appropriate answer, which it then sends

The operators of the human communications center need help. Chatbots provide it (source: unsplash.com)

Despite the development of NLP, chatbot is not easy to communicate with people. And so, even the most advanced and long-trained assistants are not infallible. Sanonymous expressions, misspellings that give new meaning to words, abbreviations or phrases that are too colloquial can be an insurmountable obstacle. Nevertheless, NLP opened the door to discussion fields for relevant and desirable virtual assistants.

And no wonder. A well-developed chatbot does a lot of work in almost any business. For example, work with it increasing sales improves the customer experience or alleviates congested operators.

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