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Sandra Maria Aluísio

Researcher at University of São Paulo

Publications -  144
Citations -  2147

Sandra Maria Aluísio is an academic researcher from University of São Paulo. The author has contributed to research in topics: Brazilian Portuguese & Sentence. The author has an hindex of 23, co-authored 138 publications receiving 1873 citations. Previous affiliations of Sandra Maria Aluísio include Spanish National Research Council.

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Proceedings ArticleDOI

Using Natural Language Processing to Build Graphical Abstracts to be used in Studies Selection Activity in Secondary Studies

TL;DR: In this paper, the authors proposed an approach composed by two pipelines: (1) triple extraction of concept-relation-concept based on NLP; and (2) attach the extracted triples in a structure used as a template to scientific studies.
Posted Content

End-To-End Speech Synthesis Applied to Brazilian Portuguese

TL;DR: The creation of publicly available resources for Brazilian Portuguese in the form of a dataset and deep learning models for end-to-end voice synthesis and it is verified that transfer learning, phonetic transcriptions and denoising are useful to train the models over the presented dataset.

Portal Min@s: Uma Ferramenta Geral de Apoio ao Processamento de Córpus de Propósito Geral (Portal Min@s: A General Purpose Support Tool for Corpora Processing)

TL;DR: This paper presents Portal, a general purpose web­based corpus processing tool which deals with different types of corpus, languages and linguistic annotations and presents the features provided by this tool and compare it with two other alternatives.
Journal ArticleDOI

Text complexity of open educational resources in Portuguese: mixing written and spoken registers in a multi-task approach

TL;DR: The main objective of this study was to explore the relationship between three text complexity tasks by jointly learning to predict text readability, using coarse and fine-grained datasets of written, spoken and domain texts (a small dataset of OER resources) to overcome the lack of grade classified resources in MEC-RED.