Research in Natural Language Processing (NLP) has rapidly
advanced in recent years, resulting in exciting algorithms for
sophisticated processing of text and speech in various languages.
Much of this work focuses on English; in this book we address
another group of interesting and challenging languages for NLP
research: the Semitic languages. The Semitic group of languages
includes Arabic (206 million native speakers), Amharic (27
million), Hebrew (7 million), Tigrinya (6.7 million), Syriac (1
million) and Maltese (419 thousand). Semitic languages exhibit
unique morphological processes, challenging syntactic constructions
and various other phenomena that are less prevalent in other
natural languages. These challenges call for unique solutions, many
of which are described in this book.
The 13 chapters presented in this book bring together leading
scientists from several universities and research institutes
worldwide. While this book devotes some attention to cutting-edge
algorithms and techniques, its primary purpose is a thorough
explication of best practices in the field. Furthermore, every
chapter describes how the techniques discussed apply to Semitic
languages. The book covers both statistical approaches to NLP,
which are dominant across various applications nowadays and the
more traditional, rule-based approaches, that were proven useful
for several other application domains. We hope that this book will
provide a "one-stop-shop'' for all the requisite background and
practical advice when building NLP applications for Semitic
languages.
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