34.621, Review: Computational Linguistics, Translation: Kenny (2022)

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LINGUIST List: Vol-34-621. Mon Feb 20 2023. ISSN: 1069 - 4875.

Subject: 34.621, Review: Computational Linguistics, Translation: Kenny (2022)

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Date: Mon, 20 Feb 2023 20:49:16
From: Polina Zorina [zorina at uni-bremen.de]
Subject: Machine translation for everyone: Empowering users in the age of artificial intelligence

 
Discuss this message:
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Book announced at http://linguistlist.org/issues/33/33-2447.html

EDITOR: Dorothy  Kenny
TITLE: Machine translation for everyone: Empowering users in the age of artificial intelligence
SERIES TITLE: Translation and Multilingual Natural Language Processing
PUBLISHER: Language Science Press
YEAR: 2022

REVIEWER: Polina Zorina, University of Bremen, Germany

SUMMARY

The book begins with an introduction by Dorothy Kenny, in which she explains
the rationale for the book and the need for machine translation literacy in
today's world. She argues that while machine translation can offer many
benefits, it is essential that users understand how the technology works and
how to use it intelligently to avoid common pitfalls. She also highlights the
ethical issues that arise when using machine translation, and the need for
users to be aware of these issues. The editor’s point of view is that all
users of machine translation should have some basic understanding of why the
technology is important and where the usage of it is appropriate with regard
to the multilingualism maintenance. She claims not to assume any prior
knowledge of machine translation and translation in general.
Kenny moves on to more technical aspects of machine translation. She describes
these technologies without recourse to mathematical concepts. Instead, she
uses insightful explanations and metaphors that can be helpful for people to
understand some general concepts of the field. The editor then provides an
introduction to the topic of machine learning. Those readers who are
unfamiliar with the area can find the earlier chapters to be easier to
comprehend, for they are less specialized than the following chapters. Chapter
1 opens with Olga Torres-Hostench's discussion on the meaning and usage of
multilingualism. She provides an example of the European Union and the role of
multilingualism there, as well as discussing the integration of machine
translation into language acquisition. This chapter helps readers to
understand the importance of multilingualism and how machine translation can
be used to promote it.
Chapter 2 is devoted to a discussion of machine translation and translation in
general. The author, Dorothy Kenny, sheds light on how translation is actually
being performed and lists the most popular myths about translation to give
readers a greater exposure to the matter and to prepare them for further
reading. The chapter provides an overview of the different approaches to
machine translation, including machine learning and artificial intelligence,
and explains the basic concepts behind these approaches. This chapter is
essential reading for anyone who wants to understand how machine translation
works. The author introduces contemporary approaches to machine translation,
i.e. machine learning and artificial intelligence, as well as basic concepts
behind these approaches.
Chapter 3, written by Caroline Rossi and Alice Carre, focuses on machine
translation evaluation. The authors stress the scientific and economic
importance of this area, and provide readers with an understanding of the
different methods used to evaluate machine translation systems. This chapter
is important for anyone who wants to be able to assess the quality of machine
translation output.
Chapter 4, written by Pilar Sanchez-Gijon and Dorothy Kenny, describes the
possible ways of making translation easier for machines beforehand. The
authors provide an overview of the different techniques used to prepare source
text for machine translation, including pre-editing and terminology
management. This chapter is essential reading for anyone who wants to use
machine translation effectively.
Chapter 5, written by Sharon O'Brien, highlights the possible ways to improve
the output of machine translation. The author specifically employs the term
''post-editing,'' which refers to the process of editing
machine translation output to improve its quality. This chapter is important
for anyone who wants to improve the quality of machine translation output.
In Chapter 6 of the book, Joss Moorkens delves into the complex and
multifaceted issues that can potentially arise with the use of machine
translation technology. The chapter highlights the importance of ethical
considerations when utilizing machine translation, and explores various
concerns that can arise in this context. The author goes on to discuss the
potential impact of machine translation on the quality of human translation,
as well as the role of human translators in ensuring that ethical and quality
standards are upheld.
Moving on to Chapter 7, by Juan Antonio Perez-Ortiz, Mikel Forcada and Filipe
Sanchez- Martinez, readers are presented with a highly technical and
specialized exploration of the most common techniques used in machine
translation. While the chapter may be challenging for readers without a
technical background, it offers a comprehensive and in-depth analysis of the
field, providing readers with a detailed understanding of the underlying
principles and concepts that drive machine translation technology.
In Chapter 8, Gema Ramirez-Sanchez provides readers with a thorough overview
of the implications of custom machine translation, including the benefits and
challenges associated with developing machine translation solutions tailored
to a specific task or domain. This chapter is written for readers with at
least a basic understanding of machine learning, and offers insights into how
custom machine translation can be used to optimize translation quality and
accuracy. The chapter also touches on the potential ethical implications of
using custom machine translation, highlighting the need for transparency and
accountability in the development and implementation of these systems.
The final chapter of the volume is written by Alice Carre, Dorothy Kenny,
Caroline Rossi, Pilar Sanchez- Gijon, and Olga Torres-Hostench. The authors
summarize their ideas and come to claim that despite being controversial,
machine translation can be useful with regard to language acquisition. In
addition, the chapter presents readers with digital alternatives to machine
learning as well as with examples of machine learning being helpful in
studies.

EVALUATION

“Machine Translation for Everyone: Empowering Users in the Age of Artificial
Intelligence” is a comprehensive and accessible guide to the world of machine
translation. The volume not only provides important contributions and
cross-linguistic perspectives to the field of machine learning but also delves
into the ethics, multilingualism, and technical aspects of the technology.
Readers will undoubtedly benefit from the introduction to the volume, where
Dorothy Kenny takes care to explain the structure of the book and how to read
it. This detailed explanation helps readers navigate the contents and get a
clear idea of what to expect from the book. One of the strengths of this
volume is its broad and insightful investigation of machine translation,
covering its meaning, operationalization, and contemporary approaches. The use
of mathematical concepts in the book, while not familiar to common readers,
can be of great interest to specialists. The authors of the book have done an
excellent job of presenting the content in a way that assumes no prior
knowledge of translation or machine translation. Chapter 7, which covers
technical aspects, is presented in a way that caters to readers lacking
specific knowledge of the topic. The author provides brief descriptions of the
technologies before delving into more complex topics. The volume is
well-structured, with a certain flow and easy-to-read chapters. Each chapter
is written by an expert in the field, and the book is edited in a way that
ensures a consistent style and tone throughout. Clear explanations and helpful
examples make the chapters easy to follow. The glossary of key terms and
concepts included in the book is also useful for readers who are new to the
field of machine translation. 
The earlier chapters are easier to comprehend, and as readers follow the
narrative, it gets to be more complex. The fact that the author made it
possible to skip some specialized chapters is well-thought. Machine
translation specialists and those training to become translators can benefit
from reading the book. One of the strengths of this book is that it covers a
wide range of topics, from the basics of machine translation to the more
technical aspects of neural machine translation. The book includes chapters on
machine translation and ethics, which is an area that is often overlooked in
other books on the topic. The book is suitable for readers of all levels, from
beginners to experts, and can be used as a reference guide or a textbook for
courses on machine translation.
Overall, “Machine Translation for Everyone: Empowering Users in the Age of
Artificial Intelligence” is a well-written and comprehensive guide to machine
translation. It is essential reading for anyone interested in using machine
translation for language learning, translation, or any other purpose. The book
provides a thorough understanding of the technology, its benefits and
pitfalls, and the ethical issues that arise when using it. It is an excellent
resource for anyone who wants to become a more informed and responsible user
of machine translation.
In conclusion, this book is an excellent resource for anyone interested in
machine translation, as it offers a comprehensive understanding of the
technology, its implications, and the ethical considerations of using it. The
authors have managed to present the content in a way that is easy to
understand, making it accessible to readers of all levels. The inclusion of
technical and mathematical concepts, as well as a glossary of key terms and
concepts, makes the book useful for both beginners and experts. The volume
offers a valuable contribution to the field of machine learning and can serve
as a textbook or reference guide for anyone interested in the topic.


ABOUT THE REVIEWER

Polina Zorina is a MA sudent of Bremen University, Germany. She is currently
writing her Master thesis on shakespeare's The Taming of the Shrew. Her
research interests include literatute, translation, theater, media.





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