Abstract
People with hearing impairment typically have difficulties following conversations in multi-talker situations. Previous studies have shown that utilizing eye gaze to steer audio through beamformers could be a solution for those situations. Recent studies have shown that in-ear electrodes that capture electrooculography in the ear (EarEOG) can estimate the eye-gaze relative to the head, when the head was fixed. The head movement can be estimated using motion sensors around the ear to create an estimate of the absolute eye-gaze in the room. In this study, an experiment was designed to mimic a multi-talker situation in order to study and model the EarEOG signal when participants attempted to follow a conversation. Eleven hearing impaired participants were presented speech from the DAT speech corpus (Bo Nielsen et al., 2014), with three targets positioned at −30°, 0° and +30° azimuth. The experiment was run in two setups: one where the participants had their head fixed in a chinrest, and the other where they were free to move their head. The participants’ task was to focus their visual attention on an LED-indicated target that changed regularly. A model was developed for the relative eye-gaze estimation, taking saccades, fixations, head movement and drift from the electrode-skin half-cell into account. This model explained 90.5% of the variance of the EarEOG when the head was fixed, and 82.6% when the head was free. The absolute eye-gaze was also estimated utilizing that model. When the head was fixed, the estimation of the absolute eye-gaze was reliable. However, due to hardware issues, the estimation of the absolute eye-gaze when the head was free had a variance that was too large to reliably estimate the attended target. Overall, this study demonstrated the potential of estimating absolute eye-gaze using EarEOG and motion sensors around the ear.
Info
Journal Article, 2019
UN SDG Classification
DK Main Research Area
Science/Technology
