Morphology

Distância diacrónica automática entre variantes diatópicas do português e do espanhol

O objetivo deste trabalho é aplicar uma metodo-
logia baseada na perplexidade, para calcular automa-
ticamente a distância interlinguística entre diferentes
períodos históricos de variantes diatópicas de idiomas.

Measuring Language Distance of Isolated European Languages

Phylogenetics is a sub-field of historical linguistics whose aim is to classify a group of
languages by considering their distances within a rooted tree that stands for their historical evolution.
A few European languages do not belong to the Indo-European family or are otherwise isolated
in the European rooted tree. Although it is not possible to establish phylogenetic links using basic
strategies, it is possible to calculate the distances between these isolated languages and the rest using

A Methodology to Measure the Diachronic Language Distance between Three Languages Based on Perplexity

The aim of this paper is to apply a corpus-based methodology, based on the measure of perplexity, to automatically calculate the cross-lingual language distance between historical periods of three languages. The three historical corpora have been constructed and collected with the closest spelling to the original on a balanced basis of fiction and non-fiction.

Measuring diachronic language distance using perplexity. Application to English, Portuguese and Spanish.

The objective of this work is to set a corpus-driven methodology to quantify automatically diachronic language distance
between chronological periods of several languages. We apply a perplexity-based measure to written text representing
different historical periods of three languages: European English, European Portuguese and European Spanish. For this
purpose, we have built historical corpora for each period, which have been compiled from different open corpus sources

Weighted finite-state transducers for normalization of historical texts

This paper presents a study about methods for normalization of historical texts. The aim of these methods
is learning relations between historical and contemporary word forms. We have compiled training and test
corpora for different languages and scenarios, and we have tried to read the results related to the features
of the corpora and languages. Our proposed method, based on weighted finite-state transducers, is com-
pared to previously published ones. Our method learns to map phonological changes using a noisy channel

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