Synopsis
A project-based book that teaches beginning Python programmers how to build working, useful, and fun voice-controlled applications.
This fun, hands-on book will take your basic Python skills to the next level as you build voice-controlled apps to use in your daily life. Starting with a Python refresher and an introduction to speech-recognition/text-to-speech functionalities, you’ll soon ease into more advanced topics, like making your own modules and building working voice-controlled apps.
Each chapter scaffolds multiple projects that allow you to see real results from your code at a manageable pace, while end-of-chapter exercises strengthen your understanding of new concepts. You’ll design interactive games, like Connect Four and Tic-Tac-Toe, and create intelligent computer opponents that talk and take commands; you’ll make a real-time language translator, and create voice-activated financial-market apps that track the stocks or cryptocurrencies you are interested in. Finally, you’ll load all of these features into the ultimate virtual personal assistant – a conversational VPA that tells jokes, reads the news, and gives you hands-free control of your email, browser, music player, desktop files, and more.
Along the way, you’ll learn how to:
● Build Python modules, implement animations, and integrate live data into an app
● Use web-scraping skills for voice-controlling podcasts, videos, and web searches
● Fine-tune the speech recognition to accept a variety of input
● Associate regular tasks like opening files and accessing the web with speech commands
● Integrate functionality from other programs into a single VPA with computational knowledge engines to answer almost any question
Packed with cross-platform code examples to download, practice activities and exercises, and explainer images, you’ll quickly become proficient in Python coding in general and speech recognition/text to speech in particular.
About the Author
Dr. Mark H. Liu is an Associate Professor and director of the Master of Science in Finance Program at the University of Kentucky, where he teaches Python Predictive Analytics and runs Python workshops. He has more than 20 years of coding experience in C++, SAS, Stata, and Python, and his research has been published in many top finance journals.
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