Natural Language Processing and Computational Linguistics

Speech, Morphology and Syntax

Mohamed Zakaria Kurdi

• Publisher: Wiley-ISTE
• Year: 2016
• Print ISBN: 9781848218482
• eBook ISBN: 9781119145578
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

Natural language processing (NLP) is a scientific discipline which is found at the interface of computer science, artificial intelligence and cognitive psychology. Providing an overview of international work in this interdisciplinary field, this book gives the reader a panoramic view of both early and current research in NLP. Carefully chosen multilingual examples present the state of the art of a mature field which is in a constant state of evolution.

In four chapters, this book presents the fundamental concepts of phonetics and phonology and the two most important applications in the field of speech processing: recognition and synthesis. Also presented are the fundamental concepts of corpus linguistics and the basic concepts of morphology and its NLP applications such as stemming and part of speech tagging. The fundamental notions and the most important syntactic theories are presented, as well as the different approaches to syntactic parsing with reference to cognitive models, algorithms and computer applications.

1
Linguistic Resources for NLP

Today, the use of good linguistic resources for the development of NLP systems seems indispensable. These resources are essential for creating grammars, in the framework of symbolic approaches or to carry out the training of modules based on machine learning. However, collecting, transcribing, annotating and analyzing these resources is far from being trivial. This is why it seems sensible for us to approach these questions in an introduction to NLP. To find out more about the matter of linguistic data and corpus linguistics, a number of works and articles can be consulted, including [HAB 97, MEY 04, WIL 06a, WIL 06b] and [MEG 03].

1.1. The concept of a corpus

At this point, a definition of the term corpus is necessary, given that it is central for the subject of this section. It is important to note that research works related to both written and spoken language data is not limited to corpus linguistics. It is actually possible to use individual texts for various forms of literary, linguistic and stylistic analyses. In Latin, the word corpus means body, but when used as a source of data in linguistics, it can be interpreted as a collection of texts. To be more specific, we will quote scholarly definitions of the term corpus from the point of view of modern linguistics:

1. – A collection of linguistic data, either written texts or a transcription of recorded speech, which can be used as a starting point of linguistic description or as a means of verifying hypotheses about a language [CRY 91].
2. – A collection of naturally occurring language text, chosen to characterize a state or variety of a language [SIN 91].
3. – The corpus itself cannot be considered as a constituent of the language: it reflects the character of the artificial situation in which it has been produced and recorded [DUB 94].

From these definitions, it is clear that a corpus is a collection of data selected with a descriptive or applicative aim as its purpose. However, what exactly are these collections? What are their fundamental properties? It is generally thought that a corpus must possess a common set of fundamental properties, including representativeness, a finite size and existing in electronic format.

The problem with the representativeness of a corpus has been highlighted by Chomsky. According to him, certain entirely valid linguistic phenomena exist which might never be observed due to their rarity. Given the infinite nature of language due to the possibility of generating an infinite number of different sentences from a finite number of rules and the constant addition of neologisms in living languages, it is clear that whatever be the size of a corpus, it would be impossible to include all linguistically valid phenomena. In practice, researchers construct corpora whose size is geared to the individual needs of the research project. Thus, the phenomena that Chomsky is talking about are certainly linguistically valid from a theoretical point of view but are almost never used in everyday life. A sentence that is ten thousand words long and formed in accordance with the rules of the English language is of no interest to a researcher who is trying to construct a machine translation system from English to Arabic, for example. Furthermore, we often talk about applications which are task orientated, where we are looking to cover the linguistic forms used in an applied context, which is restricted to hotel reservations or asking for tourist information, for example. In this sort of application, even though it is impossible to be exhaustive, it is possible (even though it takes a lot of work) to reach a satisfactory level.

Often, the size of a corpus is limited to the given number of words (a million words, for example). The size of a corpus is generally predetermined in advance during the design phase. Sometimes, teams, such as Professor John Sinclair’s team at the University of Birmingham in England, update their corpus continuously (in this case, the term text collection is preferred). This continuous updating is necessary to guarantee the representativeness of a corpus across time: the opening up and the infinity of the corpus constitute a means to guarantee diachronic representativeness. Infinite corpora are particularly useful for lexicographers who are looking to include neologisms in new editions of their dictionaries.

Today, the word corpus is almost automatically associated with the word digital. Historically, the term referred mainly to printed texts or even manuscripts. The advantages of digitalization are undeniable. On the one hand, research has become much easier and results are obtained more quickly and, on the other hand, annotation can be done much more flexibly. Moreover, sometimes long-distance teamwork has become much easier. Furthermore, in view of the extreme popularity of digital technology, having data in an electronic format allows such data to be exchanged and allows paper usage to be reduced (which is a good thing given the impact of paper usage on the environment). However, this gave birth to some long-term issues related to electronic corpora such as portability. With the development of operating systems and text analysis software, it sometimes becomes difficult to access documents that were coded with old versions of software with a format that is obsolete. To get around this problem, researchers try to perpetuate their data using independent versions of platforms and of text processing software. XML markup language is one of the main languages used for the annotation of data. More specialized standards such as the EAGLES Corpus Encoding Standard and XCES are also available and are under continuous development to allow researchers to understand linguistic phenomena in a precise and reliable way.

In the field of NLP, the use of corpora is uncontested. Of course, there is a debate surrounding the place of corpora within the approach to build NLP systems, but to our knowledge, everyone is in agreement that linguistic data play a very important role in this process. Corpora are also very useful within linguistics itself, especially for those who wish to carry out a study on a specific linguistic phenomenon such as collocations, fixed expressions, as well as lexical ambiguities. Furthermore, corpora are used more and more in disciplines such as cognitive science or foreign language teaching [NES 05, GRI 06, ATW 08].

1.2. Corpus taxonomy

To establish a corpus taxonomy, many criteria can be used, such as the distinction between spoken corpora, written corpora, modern corpora, corpora of an ancient form of a language or a dialect, as well as the number of languages in a given corpus.

1.2.1. Written versus spoken

This kind of corpus is made up of a collection of written texts. Often, corpora such as these contain newspaper articles, webpages, blogs, literary or religious texts, etc. Another source of data from the Internet includes written dialogues between two people communicating on the Internet (such as in a chat) or between a person and a computer program designed specifically for this kind of activity. Often, newspaper archives such as The Guardian (for English), Le Monde (for French) and Al-Hayat (for Arabic) are also a very popular source for written texts. They are especially useful within the fields of information research and lexicography. More sophisticated corpora also exist, such as the British National Corpus (BNC), the Brown Corpus and the Susanne Corpus, which consists of 130,000 words of the Brown Corpus which have been analyzed syntactically. Written corpora can appear in many forms. These forms differ as much at the level of their structures and linguistic functions as at the...

Table of contents

• Cover
• Table of Contents
• Title
• Copyright
• Introduction
• 1 Linguistic Resources for NLP
• 2 The Sphere of Speech
• 3 Morphology Sphere
• 4 Syntax Sphere
• Bibliography
• Index
• End User License Agreement