Featured Linguist!

Jost Gippert: Our Featured Linguist!

"Buenos dias", "buenas noches" -- this was the first words in a foreign language I heard in my life, as a three-year old boy growing up in developing post-war Western Germany, where the first gastarbeiters had arrived from Spain. Fascinated by the strange sounds, I tried to get to know some more languages, the only opportunity being TV courses of English and French -- there was no foreign language education for pre-teen school children in Germany yet in those days. Read more



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What is English? And Why Should We Care?

By: Tim William Machan

To find some answers Tim Machan explores the language's present and past, and looks ahead to its futures among the one and a half billion people who speak it. His search is fascinating and important, for definitions of English have influenced education and law in many countries and helped shape the identities of those who live in them.


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Medical Writing in Early Modern English

Edited by Irma Taavitsainen and Paivi Pahta

This volume provides a new perspective on the evolution of the special language of medicine, based on the electronic corpus of Early Modern English Medical Texts, containing over two million words of medical writing from 1500 to 1700.


Academic Paper


Title: Unsupervised Learning of Natural Languages
Paper URL: http://kybele.psych.cornell.edu/~edelman/abstracts.html#pnas05
Author: Shimon Edelman
Email: click here to access email
Homepage: http://kybele.psych.cornell.edu/~edelman
Institution: Cornell University
Linguistic Field: Cognitive Science; Computational Linguistics; Language Acquisition; Psycholinguistics
Abstract: We address the problem, fundamental to linguistics, bioinformatics and certain other disciplines, of using corpora of raw symbolic sequential data to infer underlying rules that govern their production. Given a corpus of strings (such as text, transcribed speech, chromosome or protein sequence data, sheet music, etc.), our unsupervised algorithm recursively distills from it hierarchically structured patterns. The ADIOS (Automatic DIstillation of Structure) algorithm relies on a statistical method for pattern extraction and on structured generalization, two processes that have been implicated in language acquisition. It has been evaluated on artificial context-free grammars with thousands of rules, on natural languages as diverse as English and Chinese, and on protein data correlating sequence with function. This is the first time an unsupervised algorithm is shown capable of learning complex syntax, generating grammatical novel sentences, and proving useful in other fields that call for structure discovery from raw data, such as bioinformatics.
Type: Individual Paper
Status: Completed
Publication Info: Proc. Natl. Acad. Sci. 102:11629-11634 (August 16, 2005)
URL: http://kybele.psych.cornell.edu/~edelman/abstracts.html#pnas05


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