Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Hendrik Kayser"'
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-18 (2024)
Abstract Selective attention is a crucial ability of the auditory system. Computationally, following an auditory object can be illustrated as tracking its acoustic properties, e.g., pitch, timbre, or location in space. The difficulty is related to th
Externí odkaz:
https://doaj.org/article/f43f055d4c874205840a1305dd583f87
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Recent advancements in neuroscientific research and miniaturized ear-electroencephalography (EEG) technologies have led to the idea of employing brain signals as additional input to hearing aid algorithms. The information acquired through EEG could p
Externí odkaz:
https://doaj.org/article/2ab0b5d70ad14480921ca3d386c7c0ff
Publikováno v:
SoftwareX, Vol 17, Iss , Pp 100953- (2022)
open Master Hearing Aid (openMHA) was developed and provided to the hearing aid research community as an open-source software platform with the aim to support sustainable and reproducible research towards improvement and new types of assistive hearin
Externí odkaz:
https://doaj.org/article/e189d4dbe0ca427b8d66faa5b412d873
Publikováno v:
J Acoust Soc Am
Humans are able to follow a speaker even in challenging acoustic conditions. The perceptual mechanisms underlying this ability remain unclear. A computational model of attentive voice tracking, consisting of four computational blocks: (1) sparse peri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f790db0599b211c40c42b7174fad2768
https://doi.org/10.1121/10.0009337
https://doi.org/10.1121/10.0009337
Publikováno v:
Current Directions in Biomedical Engineering, Vol 7, Iss 2, Pp 855-858 (2021)
Aiming to provide a portable research platform to develop algorithms for neuro-steered hearing aids, a joint hearing aid - EEG measurement setup was implemented in this work. The setup combines the miniaturized electroencephalography sensor technolog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a72c464c14f29f6d7a9cf5382881ed00
https://doaj.org/article/048bd3d7197d49b8a5a7b6103a41c537
https://doaj.org/article/048bd3d7197d49b8a5a7b6103a41c537
Publikováno v:
Acta acustica. European Acoustics Association. 6
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://explore.openaire.eu/search/publication?articleId=pmid________::a4cb6a45245def8b38bca6578b1b5dbc
https://pubmed.ncbi.nlm.nih.gov/36159631
https://pubmed.ncbi.nlm.nih.gov/36159631
Autor:
Kamil Adiloğlu, Hendrik Kayser, Regina M. Baumgärtel, Sanja Rennebeck, Mathias Dietz, Volker Hohmann
Publikováno v:
Trends in Hearing, Vol 19 (2015)
In many daily life communication situations, several sound sources are simultaneously active. While normal-hearing listeners can easily distinguish the target sound source from interfering sound sources—as long as target and interferers are spatial
Externí odkaz:
https://doaj.org/article/69a9bc35991949f38c485caae41278ac
Publikováno v:
ICHI
Despite many technological advances, hearing aids still amplify the background sounds together with the signal of interest. To understand how to process the acoustic information in an optimal way for a human listener, we have to understand why a heal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da25aecbfead4b20172be3a58bc3a9f8
https://doi.org/10.1109/ichi48887.2020.9374386
https://doi.org/10.1109/ichi48887.2020.9374386
Humans are able to follow a given speaker even in challenging acoustic conditions. The perceptual mechanisms underlying this ability remain unclear. In this study, we present a computational model of attentive voice tracking, consisting of four main
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e44567b69afc12ede941b3b182ac916
Publikováno v:
ICASSP
In this paper we investigate methods to predict word error rates in automatic speech recognition in the presence of unknown noise types, which have not been seen during training. The performance measures operate on phoneme posteriorgrams that are obt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c4835198b413ace7454a4c9d66de8ce
https://doi.org/10.1109/icassp.2017.7953174
https://doi.org/10.1109/icassp.2017.7953174