Zobrazeno 1 - 10
of 1 408
pro vyhledávání: '"Meyer Bernd"'
Labelled data are limited and self-supervised learning is one of the most important approaches for reducing labelling requirements. While it has been extensively explored in the image domain, it has so far not received the same amount of attention in
Externí odkaz:
http://arxiv.org/abs/2409.09647
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 32, pp. 4596-4606, 2024
Deep learning has the potential to enhance speech signals and increase their intelligibility for users of hearing aids. Deep models suited for real-world application should feature a low computational complexity and low processing delay of only a few
Externí odkaz:
http://arxiv.org/abs/2405.01967
Publikováno v:
Acta Acustica, Vol 6, p 25 (2022)
Current hearing aids are limited with respect to speech-specific optimization for spatial sound sources to perform speech enhancement. In this study, we therefore propose an approach for spatial detection of speech based on sound source localization
Externí odkaz:
https://doaj.org/article/e130f09188eb44369bd2df375a46de58
Binaural multichannel blind speaker separation with a causal low-latency and low-complexity approach
Autor:
Westhausen, Nils L., Meyer, Bernd T.
In this paper, we introduce a causal low-latency low-complexity approach for binaural multichannel blind speaker separation in noisy reverberant conditions. The model, referred to as Group Communication Binaural Filter and Sum Network (GCBFSnet) pred
Externí odkaz:
http://arxiv.org/abs/2312.05173
Ab initio molecular dynamics (AIMD) based on density functional theory (DFT) has become a workhorse for studying the structure, dynamics, and reactions in condensed matter systems. Currently, AIMD simulations are primarily carried out at the level of
Externí odkaz:
http://arxiv.org/abs/2309.00651
Publikováno v:
IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 32, 2024
The scarcity of labelled data makes training Deep Neural Network (DNN) models in bioacoustic applications challenging. In typical bioacoustics applications, manually labelling the required amount of data can be prohibitively expensive. To effectively
Externí odkaz:
http://arxiv.org/abs/2308.13201
Publikováno v:
Nature 592, 2021, 722-725
The state of protonation/deprotonation of surfaces has far-ranging implications in all areas of chemistry: from acid-base catalysis$^1$ and the electro- and photocatalytic splitting of water$^2$, to the behavior of minerals$^3$ and biochemistry$^4$.
Externí odkaz:
http://arxiv.org/abs/2308.11437
Autor:
Chen, Hao, Blatnik, Matthias A., Ritterhoff, Christian L., Sokolović, Igor, Mirabella, Francesca, Franceschi, Giada, Riva, Michele, Schmid, Michael, Čechal, Jan, Meyer, Bernd, Diebold, Ulrike, Wagner, Margareta
Publikováno v:
ACS Nano 16, 2022, 21163-21173
Clean oxide surfaces are generally hydrophilic. Water molecules anchor at undercoordinated surface metal atoms that act as Lewis-acid sites, and they are stabilized by H bonds to undercoordinated surface oxygens. The large unit cell of In2O3(111) pro
Externí odkaz:
http://arxiv.org/abs/2308.11404
Autor:
Westhausen, Nils L., Meyer, Bernd T.
Speech enhancement in hearing aids is a challenging task since the hardware limits the number of possible operations and the latency needs to be in the range of only a few milliseconds. We propose a deep-learning model compatible with these limitatio
Externí odkaz:
http://arxiv.org/abs/2307.08858