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pro vyhledávání: '"A, Dorszewski"'
Self-supervised speech representation models, particularly those leveraging transformer architectures, have demonstrated remarkable performance across various tasks such as speech recognition, speaker identification, and emotion detection. Recent stu
Externí odkaz:
http://arxiv.org/abs/2409.16302
Understanding how neural networks align with human cognitive processes is a crucial step toward developing more interpretable and reliable AI systems. Motivated by theories of human cognition, this study examines the relationship between \emph{convex
Externí odkaz:
http://arxiv.org/abs/2409.06362
Publikováno v:
2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP), London, United Kingdom, 2024, pp. 1-6
Speech representation models based on the transformer architecture and trained by self-supervised learning have shown great promise for solving tasks such as speech and speaker recognition, keyword spotting, emotion detection, and more. Typically, it
Externí odkaz:
http://arxiv.org/abs/2408.11858
Communicating in noisy, multi-talker environments is challenging, especially for people with hearing impairments. Egocentric video data can potentially be used to identify a user's conversation partners, which could be used to inform selective acoust
Externí odkaz:
http://arxiv.org/abs/2406.08089
Autor:
Alickovic, Emina, Dorszewski, Tobias, Christiansen, Thomas U., Eskelund, Kasper, Gizzi, Leonardo, Skoglund, Martin A., Wendt, Dorothea
Attending to the speech stream of interest in multi-talker environments can be a challenging task, particularly for listeners with hearing impairment. Research suggests that neural responses assessed with electroencephalography (EEG) are modulated by
Externí odkaz:
http://arxiv.org/abs/2302.13553
Publikováno v:
In International Journal of Industrial Ergonomics November 2023 98
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Autor:
Jakob Dieckmann, Caroline Dorszewski, Nicholas Balaresque, Axel von Freyberg, Andreas Fischer
Publikováno v:
Applied Sciences, Vol 14, Iss 3, p 1166 (2024)
The position of the laminar–turbulent flow transition affects the aerodynamic efficiency of wind turbine rotor blades. An established diagnostic tool is infrared thermography, which enables flow visualization on in-service wind turbines, including
Externí odkaz:
https://doaj.org/article/889a7bb09d5148b2bfdc54d5d5e7960c
Akademický článek
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Autor:
Dorszewski, Caroline, Dieckmann, Jakob, Balaresque, Nicholas, Freyberg, Axel V., Fischer, Andreas
Publikováno v:
Journal of Physics: Conference Series; 2024, Vol. 2767 Issue 1, p1-8, 8p