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Thomas E. Payne - One of the best experts on this subject based on the ideXlab platform.
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describing morphosyntax a guide for field Linguists
1997Co-Authors: Thomas E. PayneAbstract:Acknowledgments List of abbreviations Introduction 1. Demographic and ethnographic information 2. Morphological typology 3. Grammatical categories 4. Constituent order typology 5. Noun and noun-phrase operations 6. Predicate nominals and related constructions 7. Grammatical relations 8. Voice and valence adjusting operations 9. Other verb and veb-phrase operations 10. Pragmatically marked structures 11. Clause combinations 12. Conclusions: the language in use Appendices References Index of languages, language families, and language areas Subject index.
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describing morphosyntax a guide for field Linguists
1997Co-Authors: Thomas E. PayneAbstract:Current estimates are that around 3,000 of the 6,000 languages now spoken may become extinct during the next century. Some 4,000 of these existing languages have never been described, or described only inadequately. This book is a guide for linguistic fieldworkers who wish to write a description of the morphology and syntax of one of these many under-documented languages. It uses examples from many languages both well known and virtually unknown; it offers readers one possible outline for a grammatical description, with many questions designed to help them address the key topics. The appendices offer guidance on text and elicited data, and on sample reference grammars which readers might wish to consult.
Janet Ainsworth - One of the best experts on this subject based on the ideXlab platform.
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a lawyer s perspective ethical technical and practical considerations in the use of linguistic expert witnesses
International Journal of Speech Language and The Law, 2010Co-Authors: Janet AinsworthAbstract:Linguists engaged by attorneys sometimes find their experiences as consultants and witnesses confusing and frustrating. To some extent, this may be an inevitable consequence of the adversarial justice system, but it also can reflect Linguists’ misunderstanding of the obligations imposed by the ethical rules governing the practice of law. These rules can engender a skeptical assessment of the linguist’s expertise and analysis by the lawyers in the case - the hiring lawyer no less than opposing counsel. Discovery rules can create traps for the unwary expert that can undermine the expert’s credibility in this case and in cases in the future. While the hiring lawyer can properly explore the limits of what the expert can provide as helpful testimony, the linguist must resist the seductive lure of becoming a ‘hired gun.'
R. Harald Baayen - One of the best experts on this subject based on the ideXlab platform.
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Analyzing linguistic data: A practical introduction to statistics using R
Processing, 2008Co-Authors: R. Harald BaayenAbstract: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.
Sherilynn Nidever Jordan - One of the best experts on this subject based on the ideXlab platform.
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forensic linguistics the linguistic analyst and expert witness of language evidence in criminal trials
2002Co-Authors: Sherilynn Nidever JordanAbstract:Forensic linguistics (FL) provides consultation to lawyers through the analysis of language evidence during the pre-trial investigation. Evidence commonly analyzed by Linguists in criminal cases includes transcripts of police interviews and language crimes (such as bribery) and anonymous or questioned texts. Forensic linguistic testimony is rarely admitted into courts of law, however. A major reason for this is apparently impressionistic methods, which are examined for their objectivity. A further barrier to legal acceptance is that FL experts, like all experts testifying in court, support the claims of whichever side has hired them. Nonetheless, forensic Linguists have an ethical and professional responsibility to provide the legal community with reliable and admissible information and help prevent unfair conviction or acquittal of criminal defendants. Legal acceptance of FL expertise should increase as methods improve and as forensic Linguists adapt to legal norms. This thesis includes five parts: (1) "The Field of Forensic Linguistics"; (2) "The Evidence Forensic Linguists Analyze"; (3) "The Need to Improve Credibility in the Legal Community"; (4) "Professional and Ethical Issues and Responsibilities for Forensic Linguists"; and (5) "The Future of Forensic Linguistics." Anthrax letters are appenddd. (Contains 92 references.) (SM) Reproductions supplied by EDRS are the best that can be made from the original document. FORENSIC LINGUISTICS: THE LINGUISTIC ANALYST AND EXPERT WITNESS OF LANGUAGE EVIDENCE IN CRIMINAL TRIALS U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement ED ATIONAL RESOURCES INFORMATION CENTER (ERIC) This document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. A Thesis
Neme Alexis - One of the best experts on this subject based on the ideXlab platform.
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Une ressource sur la langue arabe pour la morphologie computationnelle basée sur le modèle sémitique
HAL CCSD, 2020Co-Authors: Neme AlexisAbstract:A natural path for Arabic morphology consists in adopting or adapting both the traditional Semitic model and finite-state technologies. On the one hand, we have to facilitate the linguist’s task of lexical encoding by proposing a familiar formalism: the Semitic model for morphology. On the other hand, computer scientists, in general, point to FSTs as standard devices for inflection; and FSTs have shown their simplicity and efficiency in inflectional morphology for European languages. Nevertheless, there are countless complexities in the implementation of this model with such a technique. This is due to the richness of Arabic morphology and to the actual details of the traditional root-and-pattern model. In fact, there is an opposition between the requirement to be faithful to the essence of the Semitic model, for the sake of lexicon encoders, and the necessity to curb the complexity of its traditional version. Yet, no trade-off has been found.Indeed, we have achieved and created from scratch a lexical resource containing 76,000 lemmatized entries, fully vowelized and manually encoded for inflectional morphology, representing more than 6 million inflected forms based on Semitic morphology and using finite-state technologies. Our resources are comprehensive, straightforward, accurate, and easy to update for a native linguist. They provide a significant advantage for data-driven or rule-based applications. For example, usual utilities for pattern matching typically apply regular expressions on texts; our resource offers more facilities, making it possible to describe large classes of forms using simple patterns: for instance, the lexical entry of a particular adjective may locate all its variations, 54 forms partially or fully vowelized, or only the feminine plural ones, for instance.Une stratégie naturelle pour la morphologie arabe consiste à adopter ou adapter à la fois le modèle sémitique traditionnel et les technologies à états finis. D’une part, nous devons faciliter la tâche de codage lexical par les linguistes en leur proposant un formalisme qui leur est familier : le modèle sémitique de la morphologie. D'un autre côté, les informaticiens, en général, désignent les transducteurs comme le dispositif de flexion le plus courant ; et les transducteurs ont fait la preuve de leur simplicité et de leur efficacité pour la morphologie flexionnelle des langues européennes. Néanmoins, il existe d'innombrables écueils dans la mise en œuvre de ce modèle avec cette technique. Cela est lié à la richesse de la morphologie arabe et aux détails effectifs du modèle traditionnel de la racine et du schème. En fait, il existe un antagonisme entre l'exigence de fidélité à l'essence du modèle sémitique, dans l'intérêt des codeurs de lexiques, et la nécessité de limiter la complexité de sa version traditionnelle. Et aucun compromis n'avait encore été trouvé.Nous avons réalisé et créé de toutes pièces une ressource lexicale contenant 76 000 entrées lemmatisées, entièrement voyellées, codées manuellement en ce qui concerne la morphologie flexionnelle, représentant plus de 6 millions de formes fléchies, basées sur la morphologie sémitique et utilisant des technologies à nombre d'états fini. Nos ressources sont complètes, simples, précises et faciles à mettre à jour pour un linguiste natif. Ils offrent un avantage significatif pour les applications basées sur des corpus ou sur des règles. Par exemple, les outils habituels de reconnaissance de motifs appliquent généralement des expressions régulières à des textes ; notre ressource offre plus de simplicité et de souplesse, permettant de décrire de grandes classes de formes en utilisant des modèles simples : par exemple, l'entrée lexicale d'un adjectif particulier peut localiser toutes ses variations, 54 formes partiellement ou entièrement voyellées, ou seulement celles au féminin pluriel, par exemple
