Book Image

Voice Application Development for Android

Book Image

Voice Application Development for Android

Overview of this book

Speech technology has been around for some time now. However, it has only more recently captured the imagination of the general public with the advent of personal assistants on mobile devices that you can talk to in your own language. The potential of voice apps is huge as a novel and natural way to use mobile devices. Voice Application Development for Android is a practical, hands-on guide that provides you with a series of clear, step-by-step examples which will help you to build on the basic technologies and create more advanced and more engaging applications. With this book, you will learn how to create useful voice apps that you can deploy on your own Android device in no time at all. This book introduces you to the technologies behind voice application development in a clear and intuitive way. You will learn how to use open source software to develop apps that talk and that recognize your speech. Building on this, you will progress to developing more complex apps that can perform useful tasks, and you will learn how to develop a simple voice-based personal assistant that you can customize to suit your own needs. For more interesting information about the book, visit http://lsi.ugr.es/zoraida/androidspeechbook
Table of Contents (19 chapters)
Voice Application Development for Android
Credits
Foreword
About the Authors
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface
Afterword
Index

Summary


This chapter has shown how to create and use grammars to check whether the user's input conforms to the words and phrases required by the app. Grammars are also used to extract a semantic representation from the user's input in terms of concepts relevant for the app. Two types of grammar were presented: a hand-crafted grammar designed by the developer to match the requirements of the app, and a statistical grammar learned from a large corpus of relevant data. Hand-crafted grammars are useful for input that is predictable and well-defined, whereas statistical grammars provide more robust performance and can handle a wider range of input that may be less well-formed.

In the chapters so far, the examples have assumed that the language used is English and that the interface is speech-only. Chapter 7, Multilingual and Multimodal Dialogs, will look at how to build apps that make use of languages other than English and other modalities in addition to speech.