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Throughout history, communication has either been verbal, written, or visual. This allowed us to participate in conversations and learn more about ourselves and the world around us. Conversations, in particular, require two different elements. Multiple people and a means of communication.
Fortunately, throughout the years, with technology advances, we’ve discovered new innovative means of communication. We have now unlocked new ways to communicate directly with our technology in a conversational environment using chatbots.
Having natural conversations with robots is now possible. Not only that, but they make our personal and professional lives easier. Indeed, today we can go on vacation and ask for a device to lower the blinds at home as if we were there, to turn on the air conditioning when we are about to arrive, to tell us how to say thank you in Mandarin or remind us of the list of tasks we have to complete.
Conversational Artificial Intelligence can be defined as the element responsible for the logic behind robots exchanges, it is the brain and soul of the chatbot. Conversational AI helps the robot lead the users to a specific goal. It allows for human-like conversations between machine and humans.
Conversational AI is powered by Natural Language Processing (NLP). NLP focuses on interpreting human language, while developers present the basic framework for how a conversation can unfold. Simply put, conversational AI and humans work together to create a virtual conversational experience in real-time through chatbots or conversational platforms. It is the evolution of artificial intelligence, which has learned to speak and listen.
Conversational AI uses the following technologies in order to understand, react and learn from interactions:
How it works is that the application receives data input from a human, which can be in the form of written or spoken words. If the information is spoken then Automatic Speech Recognition (ASR) is used transcribe the spoken words into text.
The application then uses Natural Language Understanding (NLU), which is part of NLP, to determine the meaning of the text and the intent behind it.
The system then uses dialog management in order to form a response based on its understanding of the text’s meaning. It could also use Natural Language Generation (NLG), the other element of NLP, in order to convert its response in a format that will be understood by humans.
Following this step, the application sends its response to the user (either through text or speech synthesis).
Finally, machine learning allows the application to learn and improve over time. Deep learning makes the machine more intelligent through each interaction.
Now that you know what it is, how does it benefit you? Well, in many ways:
There are various conversational AI applications:
If you’re using a chatbot, which is a conversational AI application that is less advanced, you’ve probably faced at least one of the following challenges:
When you’re dealing with sensitive data and personal information, Conversational AI applications have to be designed in very secure ways to make sure that privacy is respected.
A lot of factors can influence the conversation between a machine and a human such as language, sarcasm, slang, etc. Conversational AI systems have to adapt to constant changes in communication to be able to keep up with human conversations.
Conversational AI applications are becoming easier to use but there are still people that are not 100% comfortable with using this technology, mostly because they have little knowledge about it. Educating your customers about it can help the technology be better received for people who are not familiar with it.
Disclaimer: We encourage our blog authors to give their personal opinions. The opinions expressed in this blog are therefore those of the authors. They do not necessarily reflect the opinions or views of Botpress as a company.