How do Virtual Assistants Work?
The technological revolution has given birth to a new generation of cognitive services, and the latter are defined as what makes an application "smart" by understanding both spoken and textual content.
If we take a closer look at the core technology processing virtual assistants, we will stumble upon CAI & NLP.
Conversational AI (CAI) is a set of technologies that automates communications using text and/or speech-based virtual agents to create personalized customer experiences at scale. This enables organizations to invest more time in providing value added solutions.
NLP stands for “Natural Language Processing” and is a computer science allowing exchanges between computers and human language. It is used to translate the text submitted by the user to the bot – this process is called “parsing”. The purpose is to recognize the relevant keywords that the user has included in the request. Afterwards, the virtual agent reacts by searching for incorporated scenario-based solutions and presents the most relevant solution.
By integrating highly developed algorithms, the virtual assistant learns more about a user’s intention to further develop predictive insights and skills. This pattern recognition enables the bot to consciously teach itself from previous experiences, therefore enhancing the machine’s “deep learning” technique.
Virtual assistants are built around a combination of functions and properties to comprehend what a user "says" or "wants" and subsequently deliver the proper solution or service based on that insight. They tend to model human interactions as closely as possible, allowing them to benefit from characteristics such as emotional thinking and rational decision-making. However, they are not an exact science and can miss the mark. In this case, the virtual digital assistant introduces the user to a real agent in order to achieve failed tasks or to solve misunderstandings.