Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

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Modern Applied Statistics With S

Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data This textbook provides a straightforward introduction to the statistical analysis of language Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data

Analyzing linguistic data : a practical introduction to statistics using R

A catalogue record for this book is available from the British Library ISBN 0 521 82347 1 hardback ISBN 0 521 53032 6 paperback Contents List of tables page vii Preface to the second edition ix Preface to the first edition xii 1 Why a global language? 1 What is a global language? 3 What makes a global language? 7 Why do we need a global language? 11 What are the dangers of a global language? 14 Could anything stop a global language? 25 A critical era 27 2 Why English? The historical context 29 Origins 30 America 31 Canada 36 The Caribbean 39 Australia and New Zealand 40 South Africa 43 South Asia 46 Former colonial Africa 49 Southeast Asia and the South Pacific 54 A world view 59 v Contents

English as a global language

Child psychiatrists, pediatricians, and other child clinicians need to have a solid understanding of child language development. There are at least four important reasons that make this necessary. First, slowing, arrest, and deviation of language development are highly associated with, and complicate the course of, child psychopathology. Second, language competence plays a crucial role in emotional and mood regulation, evaluation, and therapy. Third, language deficits are the most frequent underpinning of the learning disorders, ubiquitous in our clinical populations. Fourth, clinicians should not confuse the rich linguistic and dialectal diversity of our clinical populations with abnormalities in child language development. The challenge for the clinician becomes, then, how to get immersed in the captivating field of child language acquisition without getting overwhelmed by its conceptual and empirical complexity. In the past 50 years and since the seminal works of Roger Brown, Jerome Bruner, and Catherine Snow, child language researchers (often known as developmental psycholinguists) have produced a remarkable body of knowledge. Linguists such as Chomsky and philosophers such as Grice have strongly influenced the science of child language. One of the major tenets of Chomskian linguistics (known as generative grammar) is that children’s capacity to acquire language is “hardwired” with “universal grammar”—an innate language acquisition device (LAD), a language “instinct”—at its core. This view is in part supported by the assertion that the linguistic input that children receive is relatively dismal and of poor quality relative to the high quantity and quality of output that they manage to produce after age 2 and that only an advanced, innate capacity to decode and organize linguistic input can enable them to “get from here (prelinguistic infant) to there (linguistic child).” In “Constructing a Language,” Tomasello presents a contrasting theory of how the child acquires language: It is not a universal grammar that allows for language development. Rather, human cognition universals of communicative needs and vocal-auditory processing result in some language universals, such as nouns and verbs as expressions of reference and predication (p. 19). The author proposes that two sets of cognitive skills resulting from biological/phylogenetic adaptations are fundamental to the ontogenetic origins of language. These sets of inherited cognitive skills are intentionreading on the one hand and pattern-finding, on the other. Intention-reading skills encompass the prelinguistic infant’s capacities to share attention to outside events with other persons, establishing joint attentional frames, to understand other people’s communicative intentions, and to imitate the adult’s communicative intentions (an intersubjective form of imitation that requires symbolic understanding and perspective-taking). Pattern-finding skills include the ability of infants as young as 7 months old to analyze concepts and percepts (most relevant here, auditory or speech percepts) and create concrete or abstract categories that contain analogous items. Tomasello, a most prominent developmental scientist with research foci on child language acquisition and on social cognition and social learning in children and primates, succinctly and clearly introduces the major points of his theory and his views on the origins of language in the initial chapters. In subsequent chapters, he delves into the details by covering most language acquisition domains, namely, word (lexical) learning, syntax, and morphology and conversation, narrative, and extended discourse. Although one of the remaining domains (pragmatics) is at the core of his theory and permeates the text throughout, the relative paucity of passages explicitly devoted to discussing acquisition and proBOOK REVIEWS

Constructing a language: A usage-based theory of language acquisition

"You shall know a word by the company it keeps!" With this slogan, J. R. Firth drew attention to a fact that language scholars had intuitively known for a long time: In natural language, words are not combined randomly into phrases and sentences, constrained only by the rules of syntax. They have a tendency to appear in certain recurrent combinations. As there are many possible reasons for words to go together, a broad range of linguistic and extra-linguistic phenomena can be found among the recurrent combinations, making them a goldmine of information for linguistics, natural language processing and related fields. There are compound nouns ("black box"), fixed and opaque idioms ("kick the bucket"), lexical selection ("a pride of lions", "heavy smoker") and formulaic expressions ("have a nice day"). They can often tell us something about the meaning of a word or even the concept behind the word (think of combinations like "dark night" and "bright day"), an idea that has inspired latent semantic analysis and similar vector space models of word meaning.
With modern computers it is easy to extract evidence for recurrent word pairs from huge text corpora, often aided by linguistic pre-processing and annotation (so that specific combinations, e.g. noun+verb can be targeted). However, the raw data - in the form of frequency counts for word pairs – are not always meaningful as a measure for the amount of "glue" between two words. Provided that both words are sufficiently frequent, their cooccurrences might be pure coincidence. Therefore, a statistical interpretation of the frequency data is necessary, which determines the degree of statistical association between the words and whether there is enough evidence to rule out chance as a factor. For this purpose, association measures are applied, which assign a score to each word pair based on the observed frequency data. The higher this score is, the stronger and more certain the association between the two words.
Even forty years ago, at the Symposium on Statistical Association Methods for Mechanized Documentation, there was a bewildering multitude of measures to choose from, but hardly any guidelines to help with the decision. This situation hasn't changed very much over the last forty years. We are still far away from a thorough understanding of association measures and there is not even a standard reference where one could look up precise definitions and related information. My thesis aims to fill this gap.
The first, encyclopedic part of the thesis begins with a description of the formal and statistical prerequisites. Intended primarily as a reference for students and researchers, it also addresses the limits of the statistical models. The following chapter presents a comprehensive repository of association measures, which are organised into thematic groups. An explicit equation is given for each measure, using a consistent notation in terms of observed and expected frequencies.
The second, methodological part suggests new approaches to the study of association measures, with an emphasis on empirical results and intuitive understanding. A cornerstone of this approach is a geometric interpretation of cooccurrence data and association measure. Measures are visualised as surfaces in a three-dimensional "coordinate space". The properties of each measure are determined by the geometric shapes of the respective surfaces.
Empirical results are obtained from evaluation studies, which test the performance of association measures in a collocation extraction task. In addition to its relevance for real-life applications, a carefully designed evaluation can reveal important properties of the association measures. Unfortunately, it is becoming clear the evaluation results cannot easily be generalised. For this reason it is desirable to carry out more evaluation experiments under different conditions. In order to reduce the necessary amount of manual work, evaluation can be performed on random samples from a set of candidates. Appropriate significance tests correct for the higher degree of uncertainty.
Finally, there is a third, computational aspect to the thesis. It is accompanied by an open-source software toolkit, which was used to perform experiments and produce graphs for the thesis. The unique feature of this software toolkit is that the current release includes all the data, scripts and explanations needed to replicate (almost) all the results found in the book. 
Das gemeinsame Vorkommen von Wortern in naturlicher Sprache - sei es in unmittelbarer Nachbarschaft, innerhalb desselben Satzes oder in einer bestimmten syntaktischen Relation - stellt eine zentrale Wissensquelle fur die maschinelle Sprachverarbeitung dar. Frequenzdaten fur solche Kookkurrenzen konnen leicht aus Textkorpora gewonnen werden, wobei in den meisten Fallen zunachst eine linguistische Vorverarbeitung erfolgt. Eine mathematische Auswertung erlaubt dann, die Ergebnisse uber das spezifische Extraktionskorpus hinaus zu verallgemeinern und auf statistische Assoziationen zwischen den Vorkommen der beteiligten Worter in der Sprache insgesamt (oder zumindest in einer Teilsprache) zu schliesen.
Das gebrauchlichste Verfahren hierfur sind sogenannte Assoziationsmase, die ausgehend von der im Korpus ermittelten Frequenzinformation eine Bewertungszahl berechnen: je hoher dieser Wert, desto starker ist die mutmasliche Assoziation. Dabei stutzt sich das Mas lediglich auf die Kookkurrenzhaufigkeit und auf die Haufigkeiten der einzelnen Worter.
Die so gewonnene Information last sich in vielfaltiger Weise anwenden, unter anderem zur Desambiguierung von syntaktischen Analysen, zur Identifikation von Satz- und Phrasengrenzen, zur Verbesserung von stochastischen Sprachmodellen, zur Lesartendesambiguierung und anderen Klassifikationsaufgaben, sowie zur Bestimmung von semantischen Ahnlichkeiten zwischen Wortern wie Synonymie und Hyponymie. Andererseits bieten statistische Assoziationen einen wichtigen Anhaltspunkt fur die Identifikation lexikalisierter Wortverbindungen, sogenannter Kollokationen.
Bereits zur Zeit der ersten computerlinguistischen Arbeiten mit Kookkurrenzdaten und Kollokationen stand eine nahezu unuberschaubare Vielfalt von Assoziationsmasen zur Verfugung: man bediente sich bei diversen Fachgebieten, allen voran naturlich der mathematischen Statistik. Gleichzeitig war man sich der Schwierigkeit bewust, ein fur die jeweilige Aufgabe geeignetes Mas zu finden, besonders da sich die in der mathematischen Statistik angefuhrten Argumente nicht ohne weiteres auf Wortkookkurrenzen ubertragen lassen.
Vierzig Jahre spater versucht die vorliegende Arbeit nun, diese Lucke zu schliesen. In einem enzyklopadischen Teil werden zunachst die formalen und statistischen Grundlagen zusammengetragen, auf denen die Assoziationsmase basieren. Diese Aufstellung soll als Referenz fur weitere Untersuchungen und Anwendungen dienen, es werden jedoch auch die Grenzen der statistischen Modelle angesprochen. Im nachsten Kapitel folgt eine Auflistung aller dem Autor bekannten Assoziationsmase. Fur jedes Mas wird eine explizite Formel in einheitlicher Notation angegeben, um die Umsetzung in einem Computerprogramm zu erleichtern und Misverstandnisse zu vermeiden. Die Assoziationsmase sind nach ihrem mathematischen Hintergrund in Gruppen eingeteilt, um so dem Leser einen besseren Uberblick zu verschaffen. Zugleich werden feine Unterschiede und uberraschende Ahnlichkeiten zwischen den Masen hervorgehoben.
Der zweite, methodische Teil will neue Anstose fur die Forschung zur Theorie und Anwendung von Assoziationsmasen geben, mit einem Schwerpunkt auf empirische Forschung und intuitives Verstehen. Eine zentrale Rolle spielt dabei eine geometrische Interpretation der Mase, die als Flachen in einem dreidimensionalen "Haufigkeitsraum" veranschaulicht werden. Die Eigenschaften eines Assoziationsmases werden dabei durch die geometrische Form der ihm entsprechenden Flachen bestimmt. 
Neben diesem intuitiven Ansatz werden auch mathematische und empirische Methoden beschrieben. Die mathematische Diskussion liefert dabei eine theoretisch fundierte Begrundung fur den Einsatz von Haufigkeitsschwellwerten: aufgrund der besonderen Verteilung von Worthaufigkeiten (bekannt unter dem Namen Zipfsches Gesetz), sind statistische Inferenzen fur Worter oder Wortpaare, die weniger als 5 Vorkommen haben, prinzipiell unzuverlassig.
Schlieslich stellen die empirischen Untersuchungen im letzten Kapitel eine Verbindung zu Anwendungen und zum linguistischen Kollokationsbegriff her. Hier werden die Assoziationsmase zur Kollokationsextraktion eingesetzt und auf diese Weise evaluiert. Neben der praktischen Relevanz kann eine sorgfaltige Evaluation einiges uber die besonderen Eigenschaften eines Mases verraten. Leider zeigt sich immer deutlicher, das sich Evaluationsergebnisse nicht auf andere Situationen ubertragen lassen. Um eine grosere Anzahl von Evaluationsexperimenten unter verschiedenen Bedingungen durchfuhren zu konnen, wird eine Evaluationsmethode vorgeschlagen, die auf Stichproben basiert. Geeignete Signifikanztests stellen sicher, das es sich bei den Ergebnissen solcher Evaluationen nicht um zufallige "Ausrutscher" handelt.

/pdf/the-statistics-of-word-cooccurrences-word-pairs-and-2nwwdy04gy.pdf

The statistics of word cooccurrences : word pairs and collocations

This paper presents methods for a qualitative, unbiased comparison of lexical association measures and the results we have obtained for adjective-noun pairs and preposition-noun-verb triples extracted from German corpora. In our approach, we compare the entire list of candidates, sorted according to the particular measures, to a reference set of manually identified "true positives". We also show how estimates for the very large number of hapaxlegomena and double occurrences can be inferred from random samples.

/pdf/methods-for-the-qualitative-evaluation-of-lexical-u0l3f560kd.pdf

Methods for the Qualitative Evaluation of Lexical Association Measures

Corpus Workbench (CWB) is a widely-used architecture for corpus analysis, originally designed at the IMS, University of Stuttgart (Christ 1994). It consists of a set of tools for indexing, managing and querying very large corpora with multiple layers of word-level annotation. CWB’s central component is the Corpus Query Processor (CQP), an extremely powerful and efficient concordance system implementing a flexible two-level search language that allows complex query patterns to be specified both at the level of an individual word or annotation, and at the level of a fully- or partially-specified pattern of tokens. CWB and CQP are commonly used as the back-end for web-based corpus interfaces, for example, in the popular BNCweb interface to the British National Corpus (Hoffmann et al. 2008). CWB has influenced other tools, such as the Manatee software used in SketchEngine, which implements the same query language (Kilgarriff et al. 2004). This paper details recent work to update CWB for the new century. Perhaps the most significant development is that CWB version 3 is now an open source project, licensed under the GNU General Public Licence. This change has substantially enlarged the community of developers and users and has enabled us to leverage existing open-source libraries in extending CWB’s capabilities. As a result, several key improvements were made to the CWB core: (i) support for multiple character sets, most especially Unicode (in the form of UTF-8), allowing all the world’s writing systems to be utilised within a CWB-indexed corpus; (ii) support for powerful Perl-style regular expressions in CQP queries, based on the open-source PCRE library; (iii) support for a wider range of OS platforms including Mac OS X, Linux, and Windows; and (iv) support for larger corpus sizes of up to 2 billion words on 64-bit platforms. Outside the CWB core, a key concern is the user-friendliness of the interface. CQP itself can be daunting for beginners. However, it is common for access to CQP queries to be provided via a web-interface, supported in CWB version 3 by several Perl modules that give easy access to different facets of CWB/CQP functionality. The CQPweb front-end (Hardie forthcoming) has now been adopted as an integral component of CWB. CQPweb provides analysis options beyond concordancing (such as collocations, frequency lists, and keywords) by using a MySQL database alongside CQP. Available in both the Perl interface and CQPweb is the Common Elementary Query Language (CEQL), a simple-syntax set of search patterns and wildcards which puts much of the power of CQP in a form accessible to beginning students and non-corpus-linguists. The paper concludes with a roadmap for future development of the CWB (version 4 and above), with a focus on even larger corpora, full support for XML and dependency annotation, new types of query languages, and improved efficiency of complex CQP queries. All interested users are invited to help us shape the future of CWB by discussing requirements and contributing to the implementation of these features.

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Twenty-first century Corpus Workbench: Updating a query architecture for the new millennium

http://www.stefan-evert.de/PUB/EvertKrenn2005.pdf

Using small random samples for the manual evaluation of statistical association measures

This book presents a richly illustrated, hands-on discussion of one of the fastest growing fields in linguistics today. The authors address key methodological issues in corpus linguistics, such as collocations, keywords and the categorization of concordance lines. They show how these topics can be explored step-by-step with BNCweb, a user-friendly web-based tool that supports sophisticated analyses of the 100-million-word British National Corpus. Indeed, the BNC and BNCweb have been described by Geoffrey Leech as “an unparalleled combination of facilities for finding out about the English language of the present day” (Foreword). The book contains tasks and exercises, and is suitable for undergraduates, postgraduates and experienced corpus users alike.

Stefan Evert

Papers

The statistics of word cooccurrences : word pairs and collocations

Methods for the Qualitative Evaluation of Lexical Association Measures

Twenty-first century Corpus Workbench: Updating a query architecture for the new millennium

Using small random samples for the manual evaluation of statistical association measures

Corpus Linguistics with BNCweb - a Practical Guide