Head of division

Prof. Dr. Dr. Birger Kollmeier

+49 (0)441 798 5466 oder 5470

W30 3-313


Katja Warnken

+49 (0)441 798 5470

+49 (0)441 798-3902

W30 3-312

Kirsten Scheel

+49 (0)441 798-3813

+49 (0)441 798-3902

W30 3-312

Address (Mail address)

Medizinische Physik, Fakultät VI
Universität Oldenburg
26111 Oldenburg

Location / How to find us

For specific questions regarding one of our research topics, please contact the respective people directly (see staff list).

Paper 2018 Schädler Warzybok Kollmeier

Objective prediction of hearing aid benefit across listener groups using machine learning: speech recognition performance with binaural noise-reduction algorithms

Marc R. Schädler, Anna Warzybok, Birger Kollmeier (2018)
Trends in Hearing 22, 1-18, First Published April 25, 2018, doi: 10.1177/2331216518768954

The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than −20 dB could not be predicted.

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