Zobrazeno 1 - 10
of 89
pro vyhledávání: '"Jesús Villalba"'
Autor:
Anna Favaro, Laureano Moro-Velázquez, Ankur Butala, Chelsie Motley, Tianyu Cao, Robert David Stevens, Jesús Villalba, Najim Dehak
Publikováno v:
Frontiers in Neurology, Vol 14 (2023)
Motor impairments are only one aspect of Parkinson's disease (PD), which also include cognitive and linguistic impairments. Speech-derived interpretable biomarkers may help clinicians diagnose PD at earlier stages and monitor the disorder's evolution
Externí odkaz:
https://doaj.org/article/9be99e98c7b948729a6cd8c1169e215f
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2019, Iss 1, Pp 1-13 (2019)
Abstract We present a novel model adaptation approach to deal with data variability for speaker diarization in a broadcast environment. Expensive human annotated data can be used to mitigate the domain mismatch by means of supervised model adaptation
Externí odkaz:
https://doaj.org/article/ba31c624d7fb4134ace03b2bac63050e
Autor:
Bryan T. Bosworth, Iskandar A. Atakhodjaev, Michael R. Kossey, Brian C. Grubel, Daniel S. Vresilovic, Jasper R. Stroud, Neil MacFarlane, Jesús Villalba, Najim Dehak, A. Brinton Cooper, Mark A. Foster, Amy C. Foster
Publikováno v:
APL Photonics, Vol 5, Iss 1, Pp 010803-010803-12 (2020)
The hallmark of the information age is the ease with which information is stored, accessed, and shared throughout the globe. This is enabled, in large part, by the simplicity of duplicating digital information without error. Unfortunately, an ever-gr
Externí odkaz:
https://doaj.org/article/3ba42fc12441443ca55a8f5e5961e0e3
Publikováno v:
Journal of the Brazilian Society of Mechanical Sciences and Engineering. 45
The energy dissipation capacity (EDC) of most current configurations of yielding steel dampers is susceptible to be improved by applying optimization concepts. Thus, this study proposes a methodology to enhance the EDC of a slotted hollow cylinder st
Publikováno v:
Interspeech 2022.
Adversarial attacks pose a severe security threat to the state-of-the-art speaker identification systems, thereby making it vital to propose countermeasures against them. Building on our previous work that used representation learning to classify and
Autor:
Jesús Villalba, Bengt J. Borgstrom, Saurabh Kataria, Magdalena Rybicka, Carlos D. Castillo, Jaejin Cho, L. Paola García-Perera, Pedro A. Torres-Carrasquillo, Najim Dehak
Publikováno v:
The Speaker and Language Recognition Workshop (Odyssey 2022).
Autor:
Jesús Villalba, Bengt J. Borgstrom, Saurabh Kataria, Jaejin Cho, Pedro A. Torres-Carrasquillo, Najim Dehak
Publikováno v:
The Speaker and Language Recognition Workshop (Odyssey 2022).
Publikováno v:
NCT Neumología y Cirugía de Tórax. 80:204-207
Publikováno v:
IEEE Signal Processing Letters. 28:121-125
Very deep transformers outperform conventional bi-directional long short-term memory networks for automatic speech recognition (ASR) by a significant margin. However, being autoregressive models, their computational complexity is still a prohibitive
Autor:
Derly Emmanuel Fuentes-Gómez, Carlos Daniel Vera-Márquez, María de Jesús Villalba-Calderón, Juan Carlos Vázquez-Minero, Arturo Chávez-Tinoco
Publikováno v:
NCT Neumología y Cirugía de Tórax. 80:84-88