When you talk with computers then we need them to mimic human interactions and it is no use in trying to conform to how computers are made to speak properly. We require computers to speak like a human being as well as communicate the way a human does. The technology of conventional AI helps to create this thing possible by allowing artificial intelligence technologies to interact with people in way like a human. When we connect the gap between human language and computer language then it makes communication between the two very easy as well as natural. The technology is not just only one thing as it’s a set of technologies that allow computers to recognize human language as well as decipher languages. And of the leader in conversational AI in research and application is Clinc. You can read more about them by visiting their site and know how they work.
How conversational AI is worked?
Let’s look up to technologies that make conversational AI possible to get an appropriate answer. It is basically comprehended and engages in the contextual dialogue by using natural language processing (NLP)which is used by all human beings and also other AI algorithms.
The first thing it should understand is what a user is trying to say and the intent of the user’s question or query. The NLP is worked in a way to decipher meaning in the customer’s language. And how it is stated. This thing the AI will be able to understand the user’s intent even among the grammatical error, shortcuts, and idiosyncrasies. Then remember the context from one statement to the next the comprehending what is being said throughout the conversation. This ability is more unique from recognizing a keyword or phrase and answering with a canned response that was all scripted for that particular keyword.
In the next step, the conversational AI should determine the correct response which will be based on the understanding of the customer’s intent by using machine learning. As the AI technology answer, all the queries of the user over time and as human being agents help to guide its intelligence and it learns more variations of the same intent as well as the response that will be most appropriate for every intent. And after this use of NLG which stands for natural language generation, the AI generates a response in a simple format.