The number of hearing-impaired individuals is growing rapidly on a global scale, due to the increase of the elderly population. Hearing impairment can make it difficult to communicate with the world around us, and it can be so difficult that certain social situations are avoided, which can lead to isolation, cognitive decline and even depression. Therefore, it is no great surprise that how well a person can understand speech (speech intelligibility) has been a high priority when developing and fitting hearing aids. The golden standard for determining speech intelligibility is a behavioral test, where the hearing-impaired individual is introduced to speech elements and repeats back what is heard. This is not only a highly time-consuming process, but also a very subjective procedure, that has shown not to always correspond to the users experience in their daily lives.
The first step of the project is to investigate whether it is possible to measure how well speech is understood, using scalp electroencephalography (EEG). This can be done by recording EEG whilst a person is listening to speech, and then use mathematical modelling to predict the speech intelligibility, see figure 1. The next natural step will be to investigate whether it is possible to measure speech intelligibility using ear-EEG. Ear-EEG is a device used for recording electrophysiological signals using electrodes placed in the ear. The benefit of using ear-EEG is that it is possible to measure EEG in the natural environment of the user, in an unobtrusive and mobile manner. If it is possible to predict speech intelligibility using ear-EEG, the immediate benefit will be obtaining a new objective measure to evaluate, whether for example a hearing aid improvement is enhancing speech intelligibility in a lab setting. This hopefully resulting in a better speech intelligibility for the end user, and thereby closing the communication gap caused by their hearing impairment.
Figure 1: To predict speech intelligibility using EEG, EEG is recorded while a person is listening to speech. Afterwards mathematical modelling is used to predict the speech intelligibility.
The project is funded by the William Demant Foundation grant number 21-2912.
