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Vowel Length From Latin to Romance

By Michele Loporcaro

This book "draws on extensive empirical data, including from lesser known varieties" and "puts forward a new account of a well-known diachronic phenomenon."


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Letter Writing and Language Change

Edited By Anita Auer, Daniel Schreier, and Richard J. Watts

This book "challenges the assumption that there is only one 'legitimate' and homogenous form of English or of any other language" and "supports the view of different/alternative histories of the English language and will appeal to readers who are skeptical of 'standard' language ideology."


Academic Paper


Title: Learning Morphology with Morfette
Paper URL: http://www.lrec-conf.org/proceedings/lrec2008/pdf/594_paper.pdf
Author: Grzegorz ChrupaƂa
Email: click here TO access email
Homepage: http://www.lsv.uni-saarland.de/personalPages/gchrupala/index.html
Institution: Saarland University
Author: Georgiana Dinu
Email: click here TO access email
Institution: Saarland University
Author: Josef Van Genabith
Email: click here TO access email
Institution: Dublin City University
Linguistic Field: Computational Linguistics
Abstract: Morfette is a modular, data-driven, probabilistic system which learns to perform joint morphological tagging and lemmatization from morphologically annotated corpora. The system is composed of two learning modules which are trained to predict morphological tags and lemmas using the Maximum Entropy classifier. The third module dynamically combines the predictions of the Maximum-Entropy models and outputs a probability distribution over tag-lemma pair sequences. The lemmatization module exploits the idea of recasting lemmatization as a classification task by using class labels which encode mappings from word forms to lemmas. Experimental evaluation results and error analysis on three morphologically rich languages show that the system achieves high accuracy with no language-specific feature engineering or additional resources.
Type: Individual Paper
Status: Completed
Venue: LREC 2008
URL: http://www.lrec-conf.org/proceedings/lrec2008/pdf/594_paper.pdf


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