Respiration mask waveguide optimisation for maximised speech intelligibility

Both the scarcity and environmental impact of disposable face masks, as in the COVID-19 pandemic, have instigated the recent development of reusable masks. Such face masks reduce transmission of infectious agents and particulates, but often impact a user's ability to be understood when materials, such as silicone or hard polymers, are used. In this work, we present a numerical optimisation approach to optimise waveguide topology, where a waveguide is used to transmit and direct sound from the interior of the mask volume to the outside air. This approach allows acoustic energy to be maximised according to specific frequency bands, including those most relevant to human speech. We employ this method to convert a resuscitator mask, made of silicone, into respiration personal protective equipment (PPE) that maximises the speech intelligibility index (SII). We validate this approach experimentally as well, showing improved SII when using the fabricated device. Together, this design represents a unique and effective approach to utilize and adapt available apparatus to filter air while improving the ability to communicate effectively, including in healthcare settings.