Book Image

Artificial Intelligence with Python - Second Edition

By : Prateek Joshi
Book Image

Artificial Intelligence with Python - Second Edition

By: Prateek Joshi

Overview of this book

Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques.
Table of Contents (26 chapters)
24
Other Books You May Enjoy
25
Index

Working with speech signals

Speech recognition is the process of understanding the words that are spoken by humans. The speech signals are captured using a microphone and the system tries to understand the words that are being captured. Speech recognition is used extensively in human-computer interaction, smartphones, speech transcription, biometric systems, security, and more.

It is important to understand the nature of speech signals before they are analyzed. These signals happen to be complex mixtures of various signals. There are many different aspects of speech that contribute to its complexity. They include emotion, accent, language, and noise.

Because of this complexity, it is difficult to define a robust set of rules to analyze speech signals. In contrast, humans are outstanding at understanding speech even though it can have so many variations. Humans seem to do it with relative ease. For machines to do the same, we need to help them understand speech the same way...