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Python Machine Learning Cookbook

You're reading from   Python Machine Learning Cookbook 100 recipes that teach you how to perform various machine learning tasks in the real world

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Product type Paperback
Published in Jun 2016
Publisher Packt
ISBN-13 9781786464477
Length 304 pages
Edition 1st Edition
Languages
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Authors (2):
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Vahid Mirjalili Vahid Mirjalili
Author Profile Icon Vahid Mirjalili
Vahid Mirjalili
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (14) Chapters Close

Preface 1. The Realm of Supervised Learning FREE CHAPTER 2. Constructing a Classifier 3. Predictive Modeling 4. Clustering with Unsupervised Learning 5. Building Recommendation Engines 6. Analyzing Text Data 7. Speech Recognition 8. Dissecting Time Series and Sequential Data 9. Image Content Analysis 10. Biometric Face Recognition 11. Deep Neural Networks 12. Visualizing Data Index

Introduction

Speech recognition refers to the process of recognizing and understanding spoken language. Input comes in the form of audio data, and the speech recognizers will process this data to extract meaningful information from it. This has a lot of practical uses, such as voice controlled devices, transcription of spoken language into words, security systems, and so on.

Speech signals are very versatile in nature. There are many variations of speech in the same language. There are different elements to speech, such as language, emotion, tone, noise, accent, and so on. It's difficult to rigidly define a set of rules that can constitute speech. Even with all these variations, humans are really good at understanding all of this with relative ease. Hence, we need machines to understand speech in the same way.

Over the last couple of decades, researchers have worked on various aspects of speech, such as identifying the speaker, understanding words, recognizing accents, translating speech...

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