Hearing aid fitting and fine-tuning based on estimated individual traits

Abstract

Objective: A generalised concept for hearing aid fitting and fine-tuning based on estimated individual traits is presented along first implementations in this report.

Design: To estimate the individual traits, a set of auditory model-based performance measures is used to generate promising candidates within the algorithm’s parameter space for a subsequent subjective rating. For the subjective assessment, a fast and intuitive multi-stimulus test denoted as combined discrimination and classification (CoDiCl) is presented to capture user preferences for an optimised setting.

Study sample: The estimation of individual traits is shown in an exemplary manner for a multidimensional coherence-based noise reduction algorithm. The dimensionality reduction was performed using differently weighted combinations of speech intelligibility index (SII) and perceived similarity measure (PSM).

Results: Nine reasonable alternative algorithm setting candidates were extracted from a model-optimised exploration path (MOEP) for a subsequent subjective rating to potentially differentiate between listeners with different attitudes towards noise suppression and introduced distortions (i.e. “noise haters” and “distortion haters”).

Conclusions: By iteratively improving the agreement between subjective and objective assessment, an objective estimation of subjective traits using appropriate weightings of objective measures may become possible. This will potentially help to efficiently fit modern multidimensional hearing aid algorithms to the individual user.

Keywords:

• Hearing aid fitting
• fine-tuning
• dimensionality reduction
• meta-controller
• subjective evaluation
• individualisation
• candidature criteria

Acknowledgements

The authors would like to thank Jürgen Kießling for helpful advice regarding the manuscript.

Declaration of interest

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article. This work was funded by the Cluster of Excellence ‘Hearing4All’ (EXZ1077) from the German research foundation DFG and the German Ministry of Education and Research (BMBF) project “Model-based Hearing Aids” (01EZ1127D).