Results 31 to 40 of about 1,119,437 (280)

Improving Aphasic Speech Recognition by Using Novel Semi-Supervised Learning Methods on AphasiaBank for English and Spanish

Applied Sciences, 2021
Automatic speech recognition in patients with aphasia is a challenging task for which studies have been published in a few languages. Reasonably, the systems reported in the literature within this field show significantly lower performance than those ...
Iván G. Torre, Mónica Romero, Aitor Álvarez   +2 more
doaj   +1 more source

Maternal near miss in low‐resource areas [PDF]

International Journal of Gynecology & Obstetrics, 2017
AbstractObjectiveTo describe the Global Network Near‐Miss Maternal Mortality System and its application in seven sites.MethodsIn a population‐based study, pregnant women eligible for enrollment in the Maternal and Newborn Health Registry at seven sites (Democratic Republic of the Congo; Guatemala; Belagavi and Nagpur, India; Kenya; Pakistan; and Zambia)
Goldenberg, Robert L., Saleem, Sarah, Ali, Sumera Aziz, Moore, Janet L., Lokangako, Adrien, Tshefu, Antoinette, Mwenechanya, Musaku, Chomba, Elwyn, Garces, Ana, Figueroa, Lester, Goudar, Shivaprasad, Kodkany, Bhalachandra, Patel, Archana, Esamai, Fabian, Nsyonge, Paul, Harrison, Margo S., Bauserman, Melissa, Bose, Carl L., Krebs, Nancy F., Hambidge, K. Michael, Derman, Richard J., Hibberd, Patricia L., Liechty, Edward A., Wallace, Dennis D., Belizan, Jose M., Miodovnik, Menachem, Koso-Thomas, Marion, Carlo, Waldemar A., Jobe, Alan H., McClure, Elizabeth M.   +29 more
openaire   +3 more sources

Progress of the PRINCIPLE project: promoting MT for Croatian, Icelandic, Irish and Norwegian [PDF]

, 2020
This paper updates the progress made on the PRINCIPLE project, a 2-year action funded by the European Commission un-der the Connecting Europe Facility (CEF) programme.
Bago, Petra, Dunne, Jane, Gaspari, Federico, Kristmannsson, Gauti, Kåsen, Andre, McHugh, Helen, Olsen, Jon Arild, Sheridan, Dana D., Sheridan, Páraic, Tinsley, John, Way, Andy   +10 more
core  

Hierarchical Transfer Learning for Multilingual, Multi-Speaker, and Style Transfer DNN-Based TTS on Low-Resource Languages

IEEE Access, 2020
This work applies a hierarchical transfer learning to implement deep neural network (DNN)-based multilingual text-to-speech (TTS) for low-resource languages. DNN-based system typically requires a large amount of training data.
Kurniawati Azizah, Mirna Adriani, Wisnu Jatmiko   +2 more
doaj   +1 more source

Regulation of Interface Compatibility and Performance in Soft Magnetic Composites with Inorganic Insulation Layers by FePO₄ Intermediate Transition Layer

Molecules
In the fabrication of soft magnetic composites, the lattice mismatch between the inorganic insulation layer and the iron matrix often leads to the formation of cracks during the molding process, which significantly impairs the operational performance of ...
Sanao Huang, Junjie Ma, Yang Liu, Hao He, Peisheng Lyu, Huaqin Huang, Bing Dai   +6 more
doaj   +1 more source

Neonatal Hypothermia in Low-Resource Settings [PDF]

Seminars in Perinatology, 2010
Hypothermia among newborns is considered an important contributor to neonatal morbidity and mortality in low-resource settings. However, in these settings only limited progress has been made towards understanding the risk of mortality after hypothermia, describing how this relationship is dependent on both the degree or severity of exposure and the ...
openaire   +2 more sources

Trivial Transfer Learning for Low-Resource Neural Machine Translation

, 2018
Transfer learning has been proven as an effective technique for neural machine translation under low-resource conditions. Existing methods require a common target language, language relatedness, or specific training tricks and regimes.
Bojar, Ondřej, Kocmi, Tom
core   +1 more source

Transfer Learning, Style Control, and Speaker Reconstruction Loss for Zero-Shot Multilingual Multi-Speaker Text-to-Speech on Low-Resource Languages

IEEE Access, 2022
Deep neural network (DNN)-based systems generally require large amounts of training data, so they have data scarcity problems in low-resource languages.
Kurniawati Azizah, Wisnu Jatmiko
doaj   +1 more source

Endangered Languages are not Low-Resourced [PDF]

, 2021
The term low-resourced has been tossed around in the field of natural language processing to a degree that almost any language that is not English can be called "low-resourced"; sometimes even just for the sake of making a mundane or mediocre paper appear more interesting and insightful.
openaire   +3 more sources

The Development of a Kazakh Speech Recognition Model Using a Convolutional Neural Network with Fixed Character Level Filters

Big Data and Cognitive Computing, 2023
This study is devoted to the transcription of human speech in the Kazakh language in dynamically changing conditions. It discusses key aspects related to the phonetic structure of the Kazakh language, technical considerations in collecting the ...
Nurgali Kadyrbek, Madina Mansurova, Adai Shomanov, Gaukhar Makharova   +3 more
doaj   +1 more source