Speech Tracking in Complex Auditory Scenes with Differentiated In- and Out-Field-Of-View Processing in Hearing Aids.

In naturalistic auditory scenes, relevant information is rarely concentrated at a single location, but rather unpredictably scattered in- and out-field-of-view (in-/out-FOV). Although the parsing of a complex auditory scene is a fairly simple job for a healthy human auditory system, the uncertainty represents a major issue in the development of effective hearing aid (HA) processing strategies. Whereas traditional omnidirectional microphones (OM) amplify the complete auditory scene without enhancing signal-to-noise-ratio (SNR) between in- and out-FOV streams, directional microphones (DM) may greatly increase SNR at the cost of preventing HA users to perceive out-FOV information. The present study compares the conventional OM and DM HA settings to a split processing (SP) scheme differentiating between in- and out-FOV processing. We recorded electroencephalographic data of ten young, normal-hearing listeners who solved a cocktail-party-scenario-paradigm with continuous auditory streams and analyzed neural tracking of speech with a stimulus reconstruction (SR) approach. While results for all settings exhibited significantly higher SR accuracies for attended in-FOV than unattended out-FOV streams, there were distinct differences between settings. In-FOV SR performance was dominated by DM and SP and out-FOV SR accuracies were significantly higher for SP compared to OM and DM. Our results demonstrate the potential of a SP approach to combine the advantages of traditional OM and DM settings without introduction of significant compromises.

Towards Contactless Estimation of Electrodermal Activity Correlates.

This paper presents a proof-of-concept for contactless and nonintrusive estimation of electrodermal activity (EDA) correlates using a camera. RGB video of the palm under three different lighting conditions showed that for a suitably chosen illumination strategy the data from the camera is sufficient to estimate EDA correlates which agree with the measurements done using laboratory grade physiological sensors. The effects we see in the recorded video can be attributed to sweat gland activity, which inturn is known to be correlated with EDA. These effects are so pronounced that simple pixel statistics can be used to quantify them. Such a method benefits from advances in computer vision and graphics research and has the potential to be used in affective computing and psychophysiology research where contact based sensors may not be suitable.