Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Fisher database"'
Publikováno v:
SLTU
Procedia Computer Science
Procedia Computer Science
This study investigates the behavior of a feature extraction neural network model trained on a large amount of single language data (“source language”) on a set of under-resourced target languages. The coverage of the source language acoustic spa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::561d2aec6e41cac756337fe497441f01
https://doi.org/10.1016/j.procs.2016.04.024
https://doi.org/10.1016/j.procs.2016.04.024
Conference
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Publikováno v:
Advanced Composites & Hybrid Materials; Dec2023, Vol. 6 Issue 6, p1-21, 21p
Autor:
Yunhui Du, Yanru Duan, Jianli Zhao, Caihong Liu, Zhen Zhang, Zhang, John, Zhijun Meng, Xiaoliang Wang, Lau, Wayne Bond, Dina Xie, Lopez, Bernard L., Christopher, Theodore A., Erhe Gao, Koch, Walter W., Huirong Liu, Demin Liu, Xin-Liang Ma, Guoqiang Gu, Yajing Wang
Publikováno v:
Arteriosclerosis, Thrombosis & Vascular Biology; Dec2023, Vol. 43 Issue 12, pe491-e508, 18p
Autor:
Hickey, Kelsey L., Swarup, Sharan, Smith, Ian R., Paoli, Julia C., Miguel Whelan, Enya, Paulo, Joao A., Harper, J. Wade
Publikováno v:
Nature; Nov2023, Vol. 623 Issue 7985, p167-174, 8p
Autor:
Ferreira, Charles Samuel Moraes, de Mesquita, David Carvalho, de Freitas Lutz, Ítalo Antônio, Veneza, Ivana Barbosa, Martins, Thaís Sousa, Santana, Paula da Conceição Praxedes, Miranda, Josy Alessandra Barreto, de Sousa, Jefferson Miranda, Matos, Suane Cristina do Nascimento, Holanda, Francisco Carlos Alberto Fonteles, da Cunha Sampaio, Maria Iracilda, Evangelista-Gomes, Grazielle Fernanda
Publikováno v:
BMC Zoology; 8/11/2023, Vol. 8 Issue 1, p1-9, 9p
Autor:
Mazel-Sanchez, Beryl, Chengyue Niu, Williams, Nathalia, Bachmann, Michael, Choltus, Hélèna, Silva, Filo, Serre-Beinier, Véronique, Karenovics, Wolfram, Iwaszkiewicz, Justyna, Zoete, Vincent, Kaiser, Laurent, Hartley, Oliver, Wehrle-Haller, Bernhard, Schmolke, Mirco
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America; 5/23/2023, Vol. 120 Issue 21, p1-11, 63p
Publikováno v:
Metabolites (2218-1989); May2023, Vol. 13 Issue 5, p654, 17p
In this paper, we present an analysis of a DNN-based autoencoder for speech enhancement, dereverberation and denoising. The target application is a robust speaker recognition system. We started with augmenting the Fisher database with artificially no
Externí odkaz:
http://arxiv.org/abs/1811.02938
In recent studies, it has shown that speaker patterns can be learned from very short speech segments (e.g., 0.3 seconds) by a carefully designed convolutional & time-delay deep neural network (CT-DNN) model. By enforcing the model to discriminate the
Externí odkaz:
http://arxiv.org/abs/1711.00366