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Over the past two years, face masks have been a critical tool for preventing the spread of COVID-19. While previous studies have examined the effects of masks on speech recognition, much of this work was conducted early in the pandemic. Given that human listeners are able to adapt to a wide variety of novel contexts in speech perception, an open question concerns the extent to which listeners have adapted to masked speech during the pandemic. In order to evaluate this, we replicated Toscano and Toscano (PLOS ONE 16(2):e0246842, 2021), looking at the effects of several types of face masks on speech recognition in different levels of multi-talker babble noise. We also examined the effects of listeners’ self-reported frequency of encounters with masked speech and the effects of the implementation of public mask mandates on speech recognition. Overall, we found that listeners’ performance in the current experiment (with data collected in 2021) was similar to that of listeners in Toscano and Toscano (with data collected in 2020) and that performance did not differ based on mask experience. These findings suggest that listeners may have already adapted to masked speech by the time data were collected in 2020, are unable to adapt to masked speech, require additional context to be able to adapt, or that talkers also changed their productions over time. Implications for theories of perceptual learning in speech are discussed.

 

Insects rely on their olfactory system to forage, prey, and mate. They can sense odorant plumes emitted from sources of their interests with their bilateral odorant antennae, and track down odor sources using their highly efficient flapping-wing mechanism. The odor-tracking process typically consists of two distinct behaviors: surging upwind and zigzagging crosswind. Despite the extensive numerical and experimental studies on the flying trajectories and wing flapping kinematics during odor tracking flight, we have limited understanding of how the flying trajectories and flapping wings modulate odor plume structures. In this study, a fully coupled three-way numerical solver is developed, which solves the 3D Navier-Stokes equations coupled with equations of motion for the passive flapping wings, and the odorant convection-diffusion equation. This numerical solver is applied to investigate the unsteady flow field and the odorant transport phenomena of a fruit fly model in both surging upwind and zigzagging crosswind cases. The unsteady flow generated by flapping wings perturbs the odor plume structure and significantly impacts the odor intensity at the olfactory receptors (i.e., antennae). During zigzagging crosswind flight, the differences in odor perception time and peak odor intensity at the receptors potentially help create stereo odorant mapping to track odor source. Our simulation results will provide new insights into the mechanism of how fruit flies perceive odor landscape and inspire the future design of odor-guided micro aerial vehicles (MAVs) for surveillance and detection missions.

 

Insects rely on their olfactory system to forage, prey, and mate. They can sense odor emitted from sources of their interest, use their highly efficient flapping-wing mechanism to follow odor trails, and track down odor sources. During such an odor-guided navigation, flapping wings not only serve as propulsors for generating lift and maneuvering, but also actively draw odors to the antennae via wing-induced flow. This helps enhance olfactory detection by mimicking “sniffing” in mammals. However, due to a lack of quantitative measuring tools and empirical evidence, we have a poor understanding of how the induced flow generated by flapping kinematics affects the odor landscape. In the current study, we designed a canonical simulation to investigate the impact of flapping motion on the odor plume structures. A sphere was placed in the upstream and releases odor at the Schmidt number of 0.71 and Reynolds number of 200. In the downstream, an ellipsoidal airfoil underwent a pitch-plunge motion. Both two- and three-dimensional cases are simulated with Strouhal number of 0.9. An in-house immersed-boundary-method-based CFD solver was applied to investigate the effects of flapping locomotion on the wake topology and odor distribution. From our simulation results, remarkable resemblances were observed between the wake topology and odor landscape. For the 2D case, an inverse von Kármán vortex street was formed in the downstream. For the 3D case, the wake bifurcates and forms two branches of horseshoe-like vortices. The results revealed in this study have the potential to advance our understanding of the odor-tracking capability of insects navigation and lead to transformative advancements in unmanned aerial devices that will have the potential to greatly impact national security equipment and industrial applications for chemical disaster, drug trafficking detection, and GPS-denied indoor environment.