Zobrazeno 1 - 10
of 197
pro vyhledávání: '"Hugo Van Hamme"'
Autor:
Corentin Puffay, Jonas Vanthornhout, Marlies Gillis, Pieter De Clercq, Bernd Accou, Hugo Van hamme, Tom Francart
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract When a person listens to natural speech, the relation between features of the speech signal and the corresponding evoked electroencephalogram (EEG) is indicative of neural processing of the speech signal. Using linguistic representations of
Externí odkaz:
https://doaj.org/article/54dc074685ed4d84916e91202ba2b43d
Autor:
Mohammad Jalilpour Monesi, Lies Bollens, Bernd Accou, Jonas Vanthornhout, Hugo Van Hamme, Tom Francart
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 652-661 (2024)
This paper describes the auditory EEG challenge, organized as one of the Signal Processing Grand Challenges at ICASSP 2023. The challenge provides EEG recordings of 85 subjects who listened to continuous speech, as audiobooks or podcasts, while their
Externí odkaz:
https://doaj.org/article/896e855ee0ce47a1badb14a75bccdba5
Publikováno v:
Data, Vol 9, Iss 8, p 94 (2024)
Researchers investigating the neural mechanisms underlying speech perception often employ electroencephalography (EEG) to record brain activity while participants listen to spoken language. The high temporal resolution of EEG enables the study of neu
Externí odkaz:
https://doaj.org/article/ca973a938f964fca960cdfebf421f83d
Autor:
Pu Wang, Hugo Van hamme
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2023, Iss 1, Pp 1-25 (2023)
Abstract With the rise of deep learning, spoken language understanding (SLU) for command-and-control applications such as a voice-controlled virtual assistant can offer reliable hands-free operation to physically disabled individuals. However, due to
Externí odkaz:
https://doaj.org/article/4a841add5e2a4712be7f9ca586a6fd47
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract To investigate the processing of speech in the brain, commonly simple linear models are used to establish a relationship between brain signals and speech features. However, these linear models are ill-equipped to model a highly-dynamic, comp
Externí odkaz:
https://doaj.org/article/23dd2f96d090423d9cd0014e14b1b899
Autor:
Wim Boes, Hugo Van hamme
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2022, Iss 1, Pp 1-13 (2022)
Abstract Large-scale sound recognition data sets typically consist of acoustic recordings obtained from multimedia libraries. As a consequence, modalities other than audio can often be exploited to improve the outputs of models designed for associate
Externí odkaz:
https://doaj.org/article/2d21ef5e9f864105b051caeb5ef275aa
Publikováno v:
Applied Sciences, Vol 13, Iss 20, p 11291 (2023)
Speech representation models lack the ability to efficiently store semantic information and require fine tuning to deliver decent performance. In this research, we introduce a transformer encoder–decoder framework with a multiobjective training str
Externí odkaz:
https://doaj.org/article/1d242ceeacba4fd89f6e94f08f120eac
Autor:
Laura Seynaeve, Deepak Baby, Hugo Van hamme, Steven De Vleeschouwer, Patrick Dupont, Wim Van Paesschen
Publikováno v:
Brain Stimulation, Vol 13, Iss 1, Pp 267-269 (2020)
Externí odkaz:
https://doaj.org/article/68ec5e9f2f434f3bb2c80a1467bf24e7
Publikováno v:
IEEE Access, Vol 7, Pp 10546-10558 (2019)
Desirable properties of extensions of non-negative matrix factorization (NMF) include robustness in the presence of noises and outliers, ease of implementation, the guarantee of convergence, operation in an automatic fashion that trades off the balan
Externí odkaz:
https://doaj.org/article/6d4d4f4e123745e18ecf126a0d860992
Autor:
Meng Sun, Hugo Van Hamme
Publikováno v:
Journal of Systemics, Cybernetics and Informatics, Vol 10, Iss 6, Pp 94-99 (2012)
This paper aims at improving the accuracy of the non- negative matrix factorization approach to word learn- ing and recognition of spoken utterances. We pro- pose and compare three coding methods to alleviate quantization errors involved in the vecto
Externí odkaz:
https://doaj.org/article/ede473c1e2ab474bbbb5f07321182f42