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pro vyhledávání: '"Stefanel, A."'
Autor:
Gris, Lucas Rafael Stefanel, Marcacini, Ricardo, Junior, Arnaldo Candido, Casanova, Edresson, Soares, Anderson, Aluísio, Sandra Maria
Automatic speech recognition (ASR) systems play a key role in applications involving human-machine interactions. Despite their importance, ASR models for the Portuguese language proposed in the last decade have limitations in relation to the correct
Externí odkaz:
http://arxiv.org/abs/2305.14580
Autor:
Faletic, Sergej, Bitzenbauer, Philipp, Bondani, Maria, Chiofalo, Marilu, Goorney, Simon, Krijtenburg-Lewerissa, Kim, Mishina, Oxana, Muller, Rainer, Pospiech, Gesche, Ercan, Ilke, Malgieri, Massimiliano, Merzel, Avraham, Michelini, Marisa, Onorato, Pasquale, Pol, Henk, Santi, Lorenzo, Seskir, Zeki Can, Sherson, Jacob, Stadermann, Kirsten, Stefanel, Alberto, Surer, Elif, Toth, Kristof, Malo, Jorge Yago, Zabello, Olgas
The GIREP community on teaching and learning quantum physics and the Education section of the Quantum flagship project of the European Union (QTEdu) have brought together different stakeholders in the field of teaching quantum physics on all levels,
Externí odkaz:
http://arxiv.org/abs/2303.07055
Autor:
da Silva, Daniel Peixoto Pinto, Casanova, Edresson, Gris, Lucas Rafael Stefanel, Junior, Arnaldo Candido, Finger, Marcelo, Svartman, Flaviane, Raposo, Beatriz, Martins, Marcus Vinícius Moreira, Aluísio, Sandra Maria, Berti, Larissa Cristina, Teixeira, João Paulo
During the outbreak of COVID-19 pandemic, several research areas joined efforts to mitigate the damages caused by SARS-CoV-2. In this paper we present an interpretability analysis of a convolutional neural network based model for COVID-19 detection i
Externí odkaz:
http://arxiv.org/abs/2211.14372
Autor:
Gris, Lucas Rafael Stefanel, Junior, Arnaldo Candido, Santos, Vinícius G. dos, Dias, Bruno A. Papa, Leite, Marli Quadros, Svartman, Flaviane Romani Fernandes, Aluísio, Sandra
The NURC Project that started in 1969 to study the cultured linguistic urban norm spoken in five Brazilian capitals, was responsible for compiling a large corpus for each capital. The digitized NURC/SP comprises 375 inquiries in 334 hours of recordin
Externí odkaz:
http://arxiv.org/abs/2210.07852
Autor:
Junior, Arnaldo Candido, Casanova, Edresson, Soares, Anderson, de Oliveira, Frederico Santos, Oliveira, Lucas, Junior, Ricardo Corso Fernandes, da Silva, Daniel Peixoto Pinto, Fayet, Fernando Gorgulho, Carlotto, Bruno Baldissera, Gris, Lucas Rafael Stefanel, Aluísio, Sandra Maria
Automatic Speech recognition (ASR) is a complex and challenging task. In recent years, there have been significant advances in the area. In particular, for the Brazilian Portuguese (BP) language, there were about 376 hours public available for ASR ta
Externí odkaz:
http://arxiv.org/abs/2110.15731
Autor:
Gris, Lucas Rafael Stefanel, Casanova, Edresson, de Oliveira, Frederico Santos, Soares, Anderson da Silva, Junior, Arnaldo Candido
Deep learning techniques have been shown to be efficient in various tasks, especially in the development of speech recognition systems, that is, systems that aim to transcribe an audio sentence in a sequence of written words. Despite the progress in
Externí odkaz:
http://arxiv.org/abs/2107.11414
Autor:
Caetano Miguel Lemos Serrote, Lia Rejane Silveira Reiniger, Valdir Marcos Stefenon, Charlene Moro Stefanel, Karol Buuron da Silva, Ana Cristina da Fonseca Ziegler
Publikováno v:
Pesquisa Florestal Brasileira, Vol 44 (2024)
- In this study we used simulation of genetic parameters based on microsatellite data to investigate the reproductive system of three Hymenaea courbaril L. species populations. Different selfing, migration and clonal reproduction rates were tested us
Externí odkaz:
https://doaj.org/article/7d0e9f03331a4b50805ca5fe071db2d5
Autor:
Casanova, Edresson, Junior, Arnaldo Candido, Shulby, Christopher, de Oliveira, Frederico Santos, Gris, Lucas Rafael Stefanel, da Silva, Hamilton Pereira, Aluisio, Sandra Maria, Ponti, Moacir Antonelli
In this paper we present an efficient method for training models for speaker recognition using small or under-resourced datasets. This method requires less data than other SOTA (State-Of-The-Art) methods, e.g. the Angular Prototypical and GE2E loss f
Externí odkaz:
http://arxiv.org/abs/2002.11213
Akademický článek
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Autor:
SFÎCĂ, Lucian, CREȚU, Claudiu-Ștefănel, ICHIM, Pavel, HRIȚAC, Robert, BREABĂN, Iuliana-Gabriela
Publikováno v:
In Sustainable Cities and Society July 2023 94