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ABOUT THE BOOK

Natural Language Processing (NLP) is a sub-field of Artificial Intelligence, linguistics, and computer science and is concerned with the generation, recognition, and understanding of human languages, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then they utilize algorithms to extract meaning and produce results. Machine Learning and Deep Learning in Natural Language Processing aims at providing a review of current Neural Network techniques in the NLP field, in particular about Conversational Agents (chatbots), Text-to-Speech, management of non-literal content – like emotions, but also satirical expressions – and applications in the healthcare field.

NLP has the potential to be a disruptive technology in various healthcare fields, but so far little attention has been devoted to that goal. This book aims at providing some examples of NLP techniques that can, for example, restore speech, detect Parkinson’s disease, or help psychotherapists.

This book is intended for a wide audience. Beginners will find useful chapters providing a general introduction to NLP techniques, while experienced professionals will appreciate the chapters about advanced management of emotion, empathy, and non-literal content.

TABLE OF CONTENTS

Preface

Editors

Contributors

Part I Introduction

Chapter 1 Introduction to Machine Learning, Deep Learning, and Natural Language Processing

Anitha S. Pillai and Roberto Tedesco

Part II Overview of Conversational Agents

Chapter 2 Conversational Agents and Chatbots: Current Trends

Alwin Joseph and Naived George Eapen

Chapter 3 Unsupervised Hierarchical Model for Deep Empathetic Conversational Agents

Vincenzo Scotti

Part III Sentiment and Emotions

Chapter 4 EMOTRON: An Expressive Text-to-Speech

Cristian Regna, Licia Sbattella, Vincenzo Scotti, Alexander Sukhov, and Roberto Tedesco

Part IV Fake News and Satire

Chapter 5 Distinguishing Satirical and Fake News

Anna Giovannacci and Mark J. Carman

Chapter 6 Automated Techniques for Identifying Claims and Assisting Fact Checkers

Stefano Agresti and Mark J. Carman

Part V Applications in Healthcare

Chapter 7 Whisper Restoration Combining Real- and Source-Model Filtered Speech for Clinical and Forensic Applications

Francesco Roberto Dani, Sonia Cenceschi, Alice Albanesi, Elisa Colletti, and Alessandro Trivilini

Chapter 8 Analysis of Features for Machine Learning Approaches to Parkinson’s Disease Detection

Claudio Ferrante, Licia Sbattella, Vincenzo Scotti, Bindu Menon, and Anitha S. Pillai

Chapter 9 Conversational Agents, Natural Language Processing, and Machine Learning for Psychotherapy

Licia Sbattella

INDEX