PHI Latin Texts. 2013. Articles Computational Stylistic Analysis of Popular Songs of Japanese Female Singer-songwritersTakafumi Suzuki, Toyo University; Mai Hosoya, Tokyo University This study analyzes popular songs composed by Japanese female singer-songwriters.
Popular songs are a good representation of modern culture and society. Songs by female singer-songwriters account for a large portion of the current Japanese hit charts and particularly play an important role in understanding the Japanese language and communication style. Correcteur Orthographique de Latin. Text Mechanic™ - Text Manipulation Tools. Dtm-Vic / Lebart. Last modified on 08/19/2013 11:42:16 Software DtmVic: Exploratory statistical processing of complex data sets comprising both numerical and textual data.
Applications concern primarily the processing of responses to open ended questions in socio-economic sample surveys. - Special emphasis on: Complementary use of visualization techniques (Principal Component Analysis, Two-way and Multiple Correspondence Analysis) and clustering techniques (hybrid method using both hierarchical clustering and k-means technique; Self Organizing Maps (SOM). Assessments of visualization techniques: resampling techniques (bootstrap, partial bootstrap, total bootstrap, bootstrapping variables). Alpheios Texts. Digital Humanities 2012. Computational stylistics. Z:perseus-annis [Klafil] Nouns in nominative Here is how I searched for nouns in nominative. case="nominative" & POS="noun" & #1 _=_ #2.
Annis² Corpus Search. Overview - ANNIS2 - a Linguistic Database for Exploring Information Structure. Pede certo. Index Thomisticus Treebank. Croatian Dependency Treebank: homepage. Croatian Dependency Treebank is one of tasks of the project 0130418 "Development of Croatian Language Resources" supported by the Ministry of Science, Education and Sports of the Republic of Croatia. goal To build a syntactically annotated Croatian corpus of at least 100,000 tokens. method Annotation will be based on dependency analysis of sentence from the corpus.
Model of syntactic description and annotation is being taken from the Prague Dependency Treebank. GOLDVARB 2001 Users' Manual. We couldn't find the page you asked for.
It might have been moved or deleted, or you might have tried the wrong address. To find the page you wanted, you could try our A-Z, or search (see the Search box at the top-right of this page). For further assistance, please contact the Computing Help Desk:Tel 01206 872345E-mail desk (non Essex users should add @essex.ac.uk to create a full e-mail address) Error code: 404 (Page not found)
Goldvarb X. References Sankoff, David & Rousseau, Pascale (1979).
Categorical contexts and variable rules. Linguistic Annotation. This page describes tools and formats for creating and managing linguistic annotations .
`Linguistic annotation' covers any descriptive or analytic notations applied to raw language data. The basic data may be in the form of time functions -- audio, video and/or physiological recordings -- or it may be textual. The added notations may include transcriptions of all sorts (from phonetic features to discourse structures), part-of-speech and sense tagging, syntactic analysis, "named entity" identification, co-reference annotation, and so on. The focus is on tools which have been widely used for constructing annotated linguistic databases, and on the formats commonly adopted by such tools and databases.
This page began as a set of links to systems for speech annotation, and the coverage of textual annotation is still inadequate. The Cultural Heritage Language Technologies Consortium. 1.
Introduction For the past three years, the Cultural Heritage Language Technologies consortium  – situated at eight institutions in four countries  – has received funding from the National Science Foundation and the European Commission International Digital Libraries program to engage in research about the most effective ways to apply technologies and techniques from the fields of computational linguistics, natural language processing, and information retrieval technologies to challenges faced by students and scholars who are working with texts written in Greek, Latin, and Old Norse .
In its broadest terms, our work has focused in four primary areas: 1) providing access to primary source materials that are often rare and fragile, 2) helping readers understand texts written in difficult languages, 3) enabling researchers to conduct new types of scholarship, and 4) preserving digital resources for the future. A Gentle Introduction to XML. As originally published in previous editions of the Guidelines, this chapter provided a gentle introduction to `just enough' SGML for anyone to understand how the TEI used that standard.
Since then, the Gentle Guide seems to have taken on a life of its own independent of the Guidelines, having been widely distributed (and flatteringly imitated) on the web. In revising it for the present draft, the editors have therefore felt free to reduce considerably its discussion of SGML-specific matters, in favour of a simple presentation of how the TEI uses XML. The encoding scheme defined by these Guidelines may be formulated either as an application of the ISO Standard Generalized Markup Language (SGML)5 or of the more recently developed W3C Extensible Markup Language (XML)6. Concordance software: MonoConc Pro MP2.2. The software is used as part of many corpus linguistics courses and is also widely used in ESL/EFL for vocabulary learning and language learning in general.
Is networkable and operates well under a variety of Windows environments (W95 and above). Available for an educational price of $85 for a single user licence. Tapor Tools Prototype. Association for Computational Linguistics. V. A Gentle Introduction to XML - TEI P5: — Guidelines for Electronic Text Encoding and Interchange. The encoding scheme defined by these Guidelines is formulated as an application of the Extensible Markup Language (XML) (Bray et al.
(eds.) (2006)). XML is widely used for the definition of device-independent, system-independent methods of storing and processing texts in electronic form. It is now also the interchange and communication format used by many applications on the World Wide Web. In the present chapter we informally introduce some of its basic concepts and attempt to explain to the reader encountering them for the first time how and why they are used in the TEI scheme. Digital Classicist: index. Collatinus. The Latin and Ancient Greek Dependency Treebanks. The Ancient Greek and Latin Dependency Treebanks are an attempt to create a linguistic genome: a large database of Classical texts where the morphological, syntactic, and lexical information for each sentence has been explicitly encoded. The point? To put linguistic research in Greek and Latin on a new quantitative foundation. To help drive a new generation of computational analysis.
And above all, to get students and faculty both involved in the production of data that can be useful to the wider scholarly community. XQuery Introduction. XPath Introduction. TextSTAT.