Visual Facial Enhancements Can Significantly Improve Speech Perception in the Presence of Noise

Human speech perception is generally optimal in quiet environments, however it becomes more difficult and error prone in the presence of noise, such as other humans speaking nearby or ambient noise. In such situations, human speech perception is improved by
speech reading
, i.e., watching the movements of a speaker's mouth and face, either consciously as done by people with hearing loss or subconsciously by other humans. While previous work focused largely on speech perception of two-dimensional videos of faces, there is a gap in the research field focusing on facial features as seen in head-mounted displays, including the impacts of display resolution, and the effectiveness of visually enhancing a virtual human face on speech perception in the presence of noise. In this paper, we present a comparative user study (
$N=21$
) in which we investigated an audio-only condition compared to two levels of head-mounted display resolution (
$1832\times 1920$
or
$916\times 960$
pixels per eye) and two levels of the native or visually enhanced appearance of a virtual human, the latter consisting of an up-scaled facial representation and simulated lipstick (lip coloring) added to increase contrast. To understand effects on speech perception in noise, we measured participants'
speech reception thresholds
(SRTs) for each audio-visual stimulus condition. These thresholds indicate the decibel levels of the speech signal that are necessary for a listener to receive the speech correctly 50% of the time. First, we show that the display resolution significantly affected participants' ability to perceive the speech signal in noise, which has practical implications for the field, especially in social virtual environments. Second, we show that our visual enhancement method was able to compensate for limited display resolution and was generally preferred by participants. Specifically, our participants indicated that they benefited from the head scaling more than the added facial contrast from the simulated lipstick. We discuss relationships, implications, and guidelines for applications that aim to leverage such enhancements.