Build a voice-controlled virtual assistant using speech-to-text engines text-to-speech engines
and conversation modules. This book shows you how to program the virtual assistant to gather
data from the internet (weather data data from Wikipedia data mining) play music and take
notes. Each chapter covers building a mini project module to make the virtual assistant better.
You'll develop the software on Linux or OS X before transferring it to your Raspberry Pi ready
for deploying in your own home-automation or Internet of Things applications. Building a
Virtual Assistant for Raspberry Pi walks you through various STTs and TTSs and the
implementation of these components with the help of Python. After that you will start
implementing logic for handling user queries and commands so that the user can have
conversations with Melissa. You will then work to improve logic handling to detect what the
user wants Melissa to do. You will also work on building some useful applications modules for
Melissa which will allow you to gain interesting information from Melissa such as the time
weather information and data from Wikipedia. You will develop a music playing application as
well as a note taking application for Melissa laying the foundations for how Melissa can be
further extended. Finally you will learn how to deploy this software to your Raspberry Pi and
how you can further scale Melissa to make her more intelligent interactive and how you can use
her in other projects such as home automation as well. What You'll Learn Design the workflow
and discover the concepts of building a voice controlled assistant Develop modules for having
conversations with the assistant Enable the assistant to retrieve information from the internet
Build utilities like a music player and a note taking application for the virtual assistant
Integrate this software with a Raspberry Pi Who This Book Is For Anyone who has built a home
automation project with Raspberry Pi and now want to enhance it by making it voice-controlled.
The book would also interest students from computer science or related disciplines.
