Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Quinten McNamara"'
Autor:
Quinten McNamara, Joshua Dong, Nishchal Bhandari, Natalie Delworth, Miguel Jette, Piotr Zelasko, Ryan Westerman, Michelle Huang, Joseph Palakapilly, Miguel Del Rio
Commonly used speech corpora inadequately challenge academic and commercial ASR systems. In particular, speech corpora lack metadata needed for detailed analysis and WER measurement. In response, we present Earnings-21, a 39-hour corpus of earnings c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84017cda10cce5b7e0464eb6aaa6c8ac
Autor:
Alexander Braylan, Md. Mustafizur Rahman, Maarten de Rijke, Vivek Khetan, Quinten McNamara, Ye Zhang, Aaron Angert, Edward Banner, Heng-Lu Chang, Ismail Sengor Altingovde, Henna Kim, An Thanh Nguyen, Kezban Dilek Onal, Dan Xu, Brandon Dang, Matthew Lease, Byron C. Wallace, Pinar Karagoz, Tyler McDonnell
Publikováno v:
Information Retrieval Journal, 21(2-3), 111-182. Springer Netherlands
A recent “third wave” of neural network (NN) approaches now delivers state-of-the-art performance in many machine learning tasks, spanning speech recognition, computer vision, and natural language processing. Because these modern NNs often compri
Autor:
Elizabeth DuPre, John A. Lee, Jean-Baptiste Poline, Dave F. Kleinschmidt, Taylor Salo, Yaroslav O. Halchenko, Michael Hanke, Dmitry Petrov, Adina Wagner, Valerie Hayot-Sasson, Christopher J. Markiewicz, Matteo Visconti di Oleggio Castello, Alejandro de la Vega, Johan D. Carlin, Krista DeStasio, Stefan Appelhoff, Tal Yarkoni, Chris Holdgraf, Oscar Esteban, Kirstie Whitaker, Dylan M. Nielson, Ross Blair, Lee S. Tirrell, Bertrand Thirion, Michael Notter, Gregory Kiar, Isla Staden, Mainak Jas, Krzysztof J. Gorgolewski, Russell A. Poldrack, Quinten McNamara
Publikováno v:
Journal of open source software
Journal of Open Source Software
The journal of open source software 4(40), 1294-(2019). doi:10.21105/joss.01294
Journal of Open Source Software
The journal of open source software 4(40), 1294-(2019). doi:10.21105/joss.01294
Brain imaging researchers regularly work with large, heterogeneous, high-dimensional datasets. Historically, researchers have dealt with this complexity idiosyncratically, with every lab or individual implementing their own preprocessing and analysis
Publikováno v:
KDD
Feature extraction is a critical component of many applied data science workflows. In recent years, rapid advances in artificial intelligence and machine learning have led to an explosion of feature extraction tools and services that allow data scien
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c7d59824b074e14d40cba1f5bedffc9