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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: Probabilistic and Possibilistic Language Models Based on the World Wide Web
Paper URL: http://www.isca-speech.org/archive/interspeech_2009/i09_2699.html
Author: Stanislas Oger
Institution: University of Avignon
Author: Georges Linarès
Institution: University of Avignon
Linguistic Field: Computational Linguistics; Text/Corpus Linguistics
Abstract: Usually, language models are built either from a closed corpus, or by using World Wide Web retrieved documents, which are considered as a closed corpus themselves. In this paper we propose several other ways, more adapted to the nature of the Web, of using this resource for language modeling. We first start by improving an approach consisting in estimating n-gram probabilities from Web search engine statistics. Then, we propose a new way of considering the information extracted from the Web in a probabilistic framework. Then, we also propose to rely on Possibility Theory for effectively using this kind of information. We compare these two approaches on two automatic speech recognition tasks: (i) transcribing broadcast news data, and (ii) transcribing domain-specific data, concerning surgical operation film comments. We show that the two approaches are effective in different situations.
Type: Individual Paper
Status: Completed
Venue: International Speech Communication Association (ISCA)
Publication Info: Proceedings of the 10th Annual Conference of the International Speech Communication Association (InterSpeech)
URL: http://www.isca-speech.org/archive/interspeech_2009/i09_2699.html


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