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Intelligent Mobile Projects with TensorFlow

You're reading from   Intelligent Mobile Projects with TensorFlow Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788834544
Length 404 pages
Edition 1st Edition
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Author (1):
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Jeff Tang Jeff Tang
Author Profile Icon Jeff Tang
Jeff Tang
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Mobile TensorFlow FREE CHAPTER 2. Classifying Images with Transfer Learning 3. Detecting Objects and Their Locations 4. Transforming Pictures with Amazing Art Styles 5. Understanding Simple Speech Commands 6. Describing Images in Natural Language 7. Recognizing Drawing with CNN and LSTM 8. Predicting Stock Price with RNN 9. Generating and Enhancing Images with GAN 10. Building an AlphaZero-like Mobile Game App 11. Using TensorFlow Lite and Core ML on Mobile 12. Developing TensorFlow Apps on Raspberry Pi 13. Other Books You May Enjoy

Using a simple speech recognition model in Android

The TensorFlow Android example app for simple speech commands recognition, located at tensorflow/example/android, has code that does audio recording and recognition in the SpeechActivity.java file, which assumes the app needs to be always ready for new audio commands. While this certainly makes sense in some cases, it also results in code that's more complicated than the code that would do recording and recognition only after the user presses a button, like the way Apple's Siri works. In this section, we'll show you how to create a new Android app and add the minimum possible code to record users' speech commands and display recognition results. This should help you more easily integrate the model to your own Android app. But if you need to deal with the case where speech commands should always be automatically...

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