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

Grammars for speech recognition and natural language understanding


Grammars can be used for two different purposes in speech-based apps that are as follows:

  • Speech recognition: In this case, grammars (also known as language models) specify the words and phrases that the recognizer can expect. For example, if the system is dealing with cities, it should not try to recognize numbers. Speech recognition grammars, as defined by W3C available at http://www.w3.org/TR/speech-grammar/, can either be specified explicitly by the developer (hand-crafted grammars) or can be computed from language data (statistical grammars). Speech recognition grammars help to make speech recognition more accurate.

  • Natural language understanding: The idea is to take the output of the recognizer and assign a semantic interpretation (or meaning) to the words. This can be done in several ways. One method involves determining the structure of the sentence (syntactic analysis) and then assigning a semantic interpretation ...