31.3466, Books: Conversational AI: McTear

[The LINGUIST List]

LINGUIST List: Vol-31-3466. Tue Nov 10 2020. ISSN: 1069 - 4875.

Subject: 31.3466, Books: Conversational AI: McTear

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Date: Tue, 10 Nov 2020 23:06:19
From: Brent Beckley [beckley at morganclaypool.com]
Subject: Conversational AI: McTear

 


Title: Conversational AI 
Subtitle: Dialogue Systems, Conversational Agents, and Chatbots 
Series Title: Human Language Technologies  

Publication Year: 2020 
Publisher: Morgan & Claypool Publishers
	   http://www.morganclaypool.com
	

Book URL: https://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?products_id=1596 


Author: Michael McTear

Electronic: ISBN:  9781636390321 Pages: 251 Price: U.S. $ 63.96
Hardback: ISBN:  9781636390338 Pages: 251 Price: U.S. $ 99.95
Paperback: ISBN:  9781636390314 Pages: 251 Price: U.S. $ 79.95


Abstract:

This book provides a comprehensive introduction to Conversational AI. While
the idea of interacting with a computer using voice or text goes back a long
way, it is only in recent years that this idea has become a reality with the
emergence of digital personal assistants, smart speakers, and chatbots.
Advances in AI, particularly in deep learning, along with the availability of
massive computing power and vast amounts of data, have led to a new generation
of dialogue systems and conversational interfaces. Current research in
Conversational AI focuses mainly on the application of machine learning and
statistical data-driven approaches to the development of dialogue systems.
However, it is important to be aware of previous achievements in dialogue
technology and to consider to what extent they might be relevant to current
research and development. Three main approaches to the development of dialogue
systems are reviewed: rule-based systems that are handcrafted using best
practice guidelines; statistical data-driven systems based on machine
learning; and neural dialogue systems based on end-to-end learning. Evaluating
the performance and usability of dialogue systems has become an important
topic in its own right, and a variety of evaluation metrics and frameworks are
described. Finally, a number of challenges for future research are considered,
including: multimodality in dialogue systems, visual dialogue; data efficient
dialogue model learning; using knowledge graphs; discourse and dialogue
phenomena; hybrid approaches to dialogue systems development; dialogue with
social robots and in the Internet of Things; and social and ethical issues.
 



Linguistic Field(s): Computational Linguistics


Written In: English  (eng)

See this book announcement on our website: 
http://linguistlist.org/pubs/books/get-book.cfm?BookID=148733




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