Machine Learning and Deep Learning in Natural Language Processing

ISBN-13: 9781032264639 / Angielski

Anitha S. Pillai; Roberto Tedesco

Opis

Natural Language Processing (NLP) is a subset of AI, linguistics and computer science, and is concerned with generation, recognition and understanding of human language, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then 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 Natural Language Processing 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 the fields of healthcare, 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.  

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

Spis treści

Preface. Editors. Contributors. Part I Introduction. Chapter 1 Introduction to Machine Learning, Deep Learning, and Natural Language Processing. Part II Overview of Conversational Agents. Chapter 2 Conversational Agents and Chatbots: Current Trends. Chapter 3 Unsupervised Hierarchical Model for Deep Empathetic Conversational Agents. Part III Sentiment and Emotions. Chapter 4 EMOTRON: An Expressive Text-to-Speech. Part IV Fake News and Satire. Chapter 5 Distinguishing Satirical and Fake News. Chapter 6 Automated Techniques for Identifying Claims and Assisting Fact Checkers. Part V Applications in Healthcare. Chapter 7 Whisper Restoration Combining Real- and Source-Model Filtered Speech for Clinical and Forensic Applications. Chapter 8 Analysis of Features for Machine Learning Approaches to Parkinson’s Disease Detection. Chapter 9 Conversational Agents, Natural Language Processing, and Machine Learning for Psychotherapy. INDEX.

O autorze

Anitha S. Pillai is a Professor in the School of Computing Sciences, Hindustan Institute of Technology and Science, India. She obtained a Ph. D. in the area of Natural Language Processing and has 3 decades of teaching and research experience. She has authored / co-authored several papers in national and international conferences/ journals. She is also the Co-founder of AtINeu - Artificial Intelligence in Neurology focusing on the applications of AI in neurological disorders.

Roberto Tedesco earned a Ph. D. in Computer Science, in 2006 at Politecnico di Milano (Italy), where he was contract professor for the Natural Language Processing (NLP) and the Accessibility courses. He is now researcher at the Scuola universitaria professionale della Svizzera italiana (SUPSI), in Lugano (Switzerland). His research interests are NLP, assistive technologies, and HCI.