Respiration mask waveguide optimisation for maximised speech intelligibility

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