Introduction
In 1950, the British mathematician Alan Turing devised the Imitation Game, which has become known as the Turing Test and hypothesizes that if a dialog is natural enough, you might not know whether you're conversing with a human or a computer. As artificial intelligence (AI) grows ever more sophisticated, this kind of conversational interaction with applications and digital assistants is becoming more and more common, and in specific scenarios can result in human-like interactions with AI agents. Common scenarios for this kind of solution include customer support applications, reservation systems, and home automation, among others.
To realize the aspiration of the imitation game, computers need not only to be able to accept language as input (either in text or audio format), but also to be able to interpret the semantic meaning of the input - in other words, understand what is being said.
Azure AI Language service supports conversational language understanding (CLU). You can use CLU to build language models that interpret the meaning of phrases in a conversational setting. One example of a CLU application is one that's able to turn devices on and off based on speech. The application is able to take in audio input such as, "Turn the light off", and understand an action it needs to take, such as turning a light off. Many types of tasks involving command and control, end-to-end conversation, and enterprise support can be completed with Azure AI Language's CLU feature.