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David Hülsmeier
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Individual aided speech-recognition performance and predictions of benefit for listeners with impaired hearing employing FADE
MR Schädler, D Hülsmeier, A Warzybok, B Kollmeier
Trends in Hearing 24, 2331216520938929, 2020
372020
Perception of sound quality of product sounds a subjective study using a semantic differential
D Hülsmeier, L Schell-Majoor, J Rennies, S van de Par
Proceedings of the International Congress on Noise Control Engineering, 843-851, 2014
162014
Microscopic multilingual matrix test predictions using an ASR-based speech recognition model.
MR Schädler, D Hülsmeier, A Warzybok, S Hochmuth, B Kollmeier
Interspeech, 610-614, 2016
152016
A flexible data-driven audiological patient stratification method for deriving auditory profiles
S Saak, D Huelsmeier, B Kollmeier, M Buhl
Frontiers in Neurology 13, 959582, 2022
92022
Inference of the distortion component of hearing impairment from speech recognition by predicting the effect of the attenuation component
D Hülsmeier, M Buhl, N Wardenga, A Warzybok, MR Schädler, ...
International Journal of Audiology 61 (3), 205-219, 2022
92022
Simulations with FADE of the effect of impaired hearing on speech recognition performance cast doubt on the role of spectral resolution
D Hülsmeier, A Warzybok, B Kollmeier, MR Schädler
Hearing Research 395, 107995, 2020
92020
Modeling the onset advantage in musical instrument recognition
K Siedenburg, MR Schädler, D Hülsmeier
The journal of the Acoustical Society of America 146 (6), EL523-EL529, 2019
92019
Model-based integration of reverberation for noise-adaptive near-end listening enhancement
H Schepker, D Hülsmeier, J Rennies, S Doclo
Sixteenth Annual Conference of the International Speech Communication …, 2015
92015
Extension of the framework for auditory discrimination experiments (FADE) to predict the goettingen (everyday) sentence speech test
D Huelsmeier, A Warzybok, MR Schaedler
Speech Communication; 13th ITG-Symposium, 1-5, 2018
72018
Towards non-intrusive prediction of speech recognition thresholds in binaural conditions
D Huelsmeier, CF Hauth, S Roettges, P Kranzusch, J Rossbach, ...
Speech Communication; 14th ITG Conference, 1-5, 2021
62021
DARF: A data-reduced FADE version for simulations of speech recognition thresholds with real hearing aids
D Hülsmeier, MR Schädler, B Kollmeier
Hearing Research 404, 108217, 2021
62021
Extension and evaluation of a near-end listening enhancement algorithm for listeners with normal and impaired hearing
J Rennies, J Drefs, D Hülsmeier, H Schepker, S Doclo
The Journal of the Acoustical Society of America 141 (4), 2526-2537, 2017
42017
How much individualization is required to predict the individual effect of suprathreshold processing deficits? Assessing Plomp's distortion component with psychoacoustic …
D Hülsmeier, B Kollmeier
Hearing Research 426, 108609, 2022
32022
Wahrnehmung der Klangqualität von Produktgeräuschen
D Hülsmeier, L Schell-Majoor, J Rennies, S van de Par
Bachelorarbeit, Carl von Ossietzky Universität Oldenburg, Fraunhofer IDMT …, 2013
22013
How Does Inattention Influence the Robustness and Efficiency of Adaptive Procedures in the Context of Psychoacoustic Assessments via Smartphone?
C Xu, D Hülsmeier, M Buhl, B Kollmeier
Trends in Hearing 28, 23312165241288051, 2024
12024
Measurement, assessment and modeling of loudness of kindergarten noise
J Rennies, FX Nsabimana, D Hülsmeier, S Meyer
Daga, 2015
12015
Modelling speech reception thresholds and their improvements due to spatial noise reduction algorithms in bimodal cochlear implant users
A Zedan, T Jürgens, B Williges, D Hülsmeier, B Kollmeier
Hearing Research 420, 108507, 2022
2022
Simulating Impaired Hearing with the Framework for Auditory Discrimination Experiments (FADE): Towards Aided Patient Performance Prediction
D Hülsmeier
Carl von Ossietzky Universität Oldenburg, 2020
2020
Towards accurate simulations of individual speech recognition benefits with real hearing aids with FADE.
D Hülsmeier, MR Schädler, B Kollmeier
CoRR, 2020
2020
Assessing the role of onsets for musical instrument identification in an auditory modeling framework
K Siedenburg, MR Schädler, D Hülsmeier
Universitätsbibliothek der RWTH Aachen, 2019
2019
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Articles 1–20