Acurácia de um modelo fonotático de entropia máxima aplicado ao português brasileiro

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Alves, Fernando Cabral
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal da Paraíba
Brasil
Linguística
Programa de Pós-Graduação em Linguística
UFPB
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/14271
Resumo: The present work is part of the studies that seek to represent and investigate linguistic systems using mathematical models. In such context, a Maximum Entropy model of phonotactics developed by Hayes and Wilson (2008) has exhibted a high level of accuracy in relation to experimental data when applied to English, outperforming other phonotactic modelling proposals. Nevertheless, despite its good results, we are ignorant of any work in Brazil which makes use of the model or of Maximum Entropy models in general. Since the model is universal (i.e. applicable to any language), we have taken our objective to be measuring the level of accuracy of the model when applying it to Brazilian Portuguese. The text is divided into three chapters. In the first chapter, we have described in details the model to be tested. In the second one, we have presented the methodology employed to: i) apply the phonotactic model to Brazilian Portuguese; and ii) collect experimental data against which we measure the accuracy of the model predictions obtained in i). The methodological procedures involved the creation of two softwares, one for automated phonological transcription of Brazilian Portuguese and a second one for carrying out magnitude estimation experiments. Finally, in chapter three we show the results. In two applications, the correlation between model predictions and experimental data, measured by the Pearson coefficient, were found to be in the region of 0 and 0,5, thus showing a much weaker linear dependence than that found for English (0,946).