31.1420, Books: Deep Learning Approaches to Text Production: Narayan, Gardent

[The LINGUIST List]

LINGUIST List: Vol-31-1420. Tue Apr 21 2020. ISSN: 1069 - 4875.

Subject: 31.1420, Books: Deep Learning Approaches to Text Production: Narayan, Gardent

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Date: Tue, 21 Apr 2020 21:33:15
From: Brent Beckley [beckley at morganclaypool.com]
Subject: Deep Learning Approaches to Text Production: Narayan, Gardent

 


Title: Deep Learning Approaches to Text Production 
Series Title: Human Language Technologies  

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

Book URL: http://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?products_id=1520 


Author: Shashi Narayan
Author: Claire Gardent

Paperback: ISBN:  9781681737584 Pages: 199 Price: U.S. $ 79.95


Abstract:

Text production has many applications. It is used, for instance, to generate
dialogue turns from dialogue moves, verbalise the content of knowledge bases,
or generate English sentences from rich linguistic representations, such as
dependency trees or abstract meaning representations. Text production is also
at work in text-to-text transformations such as sentence compression, sentence
fusion, paraphrasing, sentence (or text) simplification, and text
summarisation. This book offers an overview of the fundamentals of neural
models for text production. In particular, we elaborate on three main aspects
of neural approaches to text production: how sequential decoders learn to
generate adequate text, how encoders learn to produce better input
representations, and how neural generators account for task-specific
objectives. Indeed, each text-production task raises a slightly different
challenge (e.g, how to take the dialogue context into account when producing a
dialogue turn, how to detect and merge relevant information when summarising a
text, or how to produce a well-formed text that correctly captures the
information contained in some input data in the case of data-to-text
generation). We outline the constraints specific to some of these tasks and
examine how existing neural models account for them. More generally, this book
considers text-to-text, meaning-to-text, and data-to-text transformations. It
aims to provide the audience with a basic knowledge of neural approaches to
text production and a roadmap to get them started with the related work. The
book is mainly targeted at researchers, graduate students, and industrials
interested in text production from different forms of inputs.
 



Linguistic Field(s): Neurolinguistics


Written In: English  (eng)

See this book announcement on our website: 
http://linguistlist.org/pubs/books/get-book.cfm?BookID=143233




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LINGUIST List: Vol-31-1420	
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