Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots by Michael McTear

Abstract

This book has appeared in the series Synthesis Lectures on Human Language Technologies: monographs from 50 up to 150 pages about specific topics subjects in computational linguistics. The intended audience of the book are researchers and graduate students in NLP, AI, and related fields. I define myself as a computational linguist; my review is from a perspective of a “random” computational linguistics researcher wanting to learn more about this topic or looking for a good guide to teach a course on dialogue systems. I found the book very easy to read and interesting and therefore I believe that McTear fully achieved his purpose to write “a readable introduction to the various concepts, issues and technologies of Conversational AI.” He succeeds remarkably well in staying on the right level of technical details, never losing the purpose of giving an overview, and the reader does not get lost in numerous details about specific algorithms. Additionally, for people who are experts in Conversational AI, the book could still be very useful because its bibliography is exceptionally complete: a very large number of early works and recent studies are cited and commented through the whole book. The book is well structured into six chapters. After an introduction, there are two chapters about specific types of dialogue systems: rule-based systems (Chapter 2) and statistical systems (Chapter 3). This is followed by a chapter about evaluation methods (Chapter 4), after which the more recent neural end-to-end systems are reviewed (Chapter 5). The book ends with a chapter on various challenges and future directions for the research on Conversational AI (Chapter 6). I found that it was meaningful to distinguish the three types of dialogue systems: rule-based systems, statistical but modular systems, and end-to-end neural systems. It might, at first, seem strange that the topic on system evaluation methods is placed between the chapter about modular statistical dialogue systems and neural end-to-end systems, but as a reader, I believe that the discussion about system evaluation comes around at the right place in the book, because it helps to better understand the difference between modular and sequence to sequence systems. In this review, I will discuss the chapters one by one in the same order as they appear in the book.