Breaking down NLP, NLU, NLG – The basics of building an AI chatbot

Chatbots have been the buzzword of the year 2017 and have greatly impacted how we communicate across the web. In 2018, it has become essential if not imperative for online businesses to integrate a conversation bot that can take user engagement to the next level and ensure a better experience for their visitors. To converse across different digital mediums, a user has to follow a set of different steps to reach the desired goal. A chatbot integrated into a website or app cuts down on these steps and makes it easy for a user to find what they are looking for. Designing conversational entities is you however not an easy feat as you need a piece of computer code to understand user intent and respond accordingly. To build AI Chatbot, developers use the technologies like NLP, NLG, and NLU to help a chatbot to understand user intent and queries and generate a correct response to their queries. 

What is NLP (Natural Language Processing)?

Natural Language Processing or NLP is the process through which a computer understands the meaning of words. In simple words, as our team leader of the chatbot design team says, “An intelligent bot understands the that hi and hello are words with similar meanings while a simple bot takes it to be two different words.” He quotes this example frequently and this is quite apt in understanding the function of NLP in making a chatbot.

What is NLU (Natural Language Understanding)?

Natural Language Understanding is kind of similar to NLP only with this, the chatbot can understand the spelling mistakes, typing errors and generate responses. With NLP the user needs to enter the words and phrases in a correct order to get the apt response from the chatbot. NLU takes the chatbots a step ahead by teaching them to understand user errors and still generate the right response. This will help to make conversations with computers more believable and guarantee user satisfaction.

What is NLG (Natural Language Generation)?

Natural Language Generation is how computers write languages by turning structured data to codes. It is a bit different from NLP or NLU but still related as it involves the response that a chatbot would give to its users once it gets a message from them.

To put it in simple words, creating a good chatbot revolves around the fact how well it is able to process the user input and carry forward a conversation. Thus, natural language processing, natural language understanding, and natural language generation need to work together in tandem to make a chatbot conversation more human-like.

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