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
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
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
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
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
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
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
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
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
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
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
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
Wahrnehmung der Klangqualität von Produktgeräuschen
D Hülsmeier, L Schell-Majoor, J Rennies, S van de Par
Bachelorarbeit, Carl von Ossietzky Universität Oldenburg, Fraunhofer IDMT …, 2014
Measurement, assessment and modeling of loudness of kindergarten noise
J Rennies, FX Nsabimana, D Hülsmeier, S Meyer
Daga, 2015
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
PsyArXiv, 2023
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
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
Simulating Impaired Hearing with the Framework for Auditory Discrimination Experiments (FADE): Towards Aided Patient Performance Prediction
D Hülsmeier
Carl von Ossietzky Universität Oldenburg, 2020
Towards accurate simulations of individual speech recognition benefits with real hearing aids with FADE.
D Hülsmeier, MR Schädler, B Kollmeier
CoRR, 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
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