Book Image

Voice User Interface Projects

By : Henry Lee
Book Image

Voice User Interface Projects

By: Henry Lee

Overview of this book

From touchscreen and mouse-click, we are moving to voice- and conversation-based user interfaces. By adopting Voice User Interfaces (VUIs), you can create a more compelling and engaging experience for your users. Voice User Interface Projects teaches you how to develop voice-enabled applications for desktop, mobile, and Internet of Things (IoT) devices. This book explains in detail VUI and its importance, basic design principles of VUI, fundamentals of conversation, and the different voice-enabled applications available in the market. You will learn how to build your first voice-enabled application by utilizing DialogFlow and Alexa’s natural language processing (NLP) platform. Once you are comfortable with building voice-enabled applications, you will understand how to dynamically process and respond to the questions by using NodeJS server deployed to the cloud. You will then move on to securing NodeJS RESTful API for DialogFlow and Alexa webhooks, creating unit tests and building voice-enabled podcasts for cars. Last but not the least you will discover advanced topics such as handling sessions, creating custom intents, and extending built-in intents in order to build conversational VUIs that will help engage the users. By the end of the book, you will have grasped a thorough knowledge of how to design and develop interactive VUIs.
Table of Contents (12 chapters)

Using Analytics

In Dialogflow, there is an Analytics section, where you can see the performance of the agent. The following data metrics are collected:

  • The number of queries per user session
  • The number of times the intent was called
  • The percentage of where user exited
  • The average response time to user requests

One of the important metrics is the number of times the intent was called, because it gives us an insight into the most popular intent in your VUIs. Once you know which intent is popular, you can continue to improve it. Also, knowing the average response time to user requests provides important information, as you would not want your user to wait a long time for a response.

The following image shows you the all the metrics collected by Dialogflow Analytics:

Dialogflow Analytics