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Master's Dissertation
DOI
https://doi.org/10.11606/D.59.2021.tde-03032021-163158
Document
Author
Full name
Lucas Pimenta Porto
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
Ribeirão Preto, 2020
Supervisor
Committee
Ruiz, Evandro Eduardo Seron (President)
Felippo, Ariani Di
Ribeiro, Evandro Marcos Saidel
Title in Portuguese
Pós-processamento de textos de tradução automática baseado em teoria de grafos
Keywords in Portuguese
Coerência textual
Teoria dos grafos
Tradução automática
Abstract in Portuguese
A tradução automática está intrinsecamente associada ao estudo e desenvolvimento de metodologias computadorizadas para a produção de traduções idiomáticas. As abordagens mais utilizadas são as abordagens estatísticas e as abordagens baseadas em redes neurais. Uma das deficiências apontadas por estes métodos é a possível falta de coerência entre as sentenças traduzidas. Neste projeto propomos a utilização de técnicas baseadas na Teoria de Grafos para conservar a coerência na tradução dos textos do Inglês para o Português. O método estudado apresenta grande variabilidade de desempenho, no entanto, algumas traduções apresentam resultados 90% melhores do que o tradutor estatístico Moses e 10% superior ao Google Tradutor.
Title in English
Post-processing of machine translation texts based on graph theory
Keywords in English
Graph theory
Machine translation
Textual coherence
Abstract in English
Machine translation is intrinsically associated with the study and development of computerized methodologies for idiomatic translations' production. The most common approaches are the statistical and methods based on neural networks. One of the deficiencies pointed out by these methods is the possible lack of coherence between the translated sentences. In this project, we propose using techniques based on Graph Theory to preserve the coherence in the translation of texts from English to Portuguese. The studied method presents large performance variability; however, some translations produce sentences 90% better evaluated than the statistical translator Moses and 10% superior to Google Translate.
 
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Publishing Date
2021-03-23
 
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