How To Make A Chatbot Using Natural Language Processing?
In the early days, chatbots were just new digital devices in the market with no practical utility and used to experiment with the market. But with time they were also evolved and thus became a vital tool in the corporate world.
The development and maintenance of a chatbot is an effort-intensive, time-consuming, and costly task. Still, many startups and established organizations are trying to experiment with this incredibly humanitarian and innovative technology.
The integration of interactive chatbots into corporate platforms or websites is very popular and used by almost every organization. These chatbots are capable of answering different and out-of-the-box questions. This device ensures that customers get all the necessary and required information anytime and anywhere.
The integration of these trendy chatbots in business websites or other platforms is inevitable. Nowadays several companies are using this system because they want their customers to have access to the right information anytime and anywhere.
Chatbots respond back to queries quickly with relevant information and thus speed up the response time. This helps companies can save a lot of money that they usually spend on customer service. It also enables agents and employees to concentrate on other challenging tasks.
Many well-known brands like MasterCard have also launched their own chatbots. From American Express’s customer service to Google Pixel’s call screening software, chatbots are transforming the corporate world in surprising and fascinating ways. This way they ensure that 24/7 availability is provided to all customers.
What Is Meant By Deep Learning Chatbot?
A deep learning chatbot uses natural language processing to map the user input to the intent in its database to categorize the message to make a predetermined response. The primary goal behind all this is to make the chatbot intelligent and behave as human as much as possible.
A chatbot is an intelligent device that enables machines to analyze, grasp, and answer through Natural Language Understanding. It is based on refined deep learning and natural language understanding (NLU).
Modern chatbots made in python using natural language processing (NLP) behave almost the same as humans and one cannot distinguish them at the front end. Our daily lives and companies can be significantly facilitated or made easier because of the use of NLP in chatbots. As chatbots can now identify the exact intent of users, just as people can comprehend each other’s language.
What Are The Different Types Of Chatbots?
Based on different programs and tools, chatbots made using natural language processing are of two types:
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Scripted chatbots:
These chatbots work on a set of pre-written rules in a conversational flow. When a user clicks one of the mentioned questions, it responds to it with the scripted answer stored in its database. If a user writes a query out of the box, this type of chatbot may not be able to answer it.?
Artificially intelligent chatbots:
These chatbots are based on natural language processing and they are made very human-like. These AI chatbots learn and expand their knowledge base with every new interaction. And this is why they are able to respond to the exact meaning of the query.
Its characteristics include communicating with humans via text messages or sound methods. And this becomes possible due to the computer program or artificial intelligence used in it. These NLP-based chatbots are usually designed to support customers on websites through the phone.
Such chatbots are used in messaging or eCommerce apps to order food/products, buy tickets, message automatically, or show weather stats. Some famous examples of apps that use AI chatbots include Slack, Telegram, eBay, Lyft, etc.
Challenges Faced By NLP-based Chatbots
Earlier computers were used for complex calculations but now they have also evolved with time. With the invention of Natural language processing, computers nowadays are capable of understanding and reacting to human language. Well, the human language is chaotic which makes it difficult for chatbots to understand and respond.
Here are some of the elements mentioned below which make the understanding of a natural language processing chatbot challenging.?
We, humans, can understand the meaning behind body language, intonation, content, and expressions. We can have an understanding of the working of a machine using NLP till it does not have such linguistic characteristics. NLP suggests teaching the machines to understand the speech irrespective of distractors.