Living in a world where machines are talking to us with synthetic voices, it is important to discuss questions of representation and aesthetics. Today most voices in devices and systems are designed to have binary vocal identities. This could be different. Our project aims to inspire a reimagination of the paralinguistics of synthesized voices, exploring how to train and develop the pitch, timbre, pace, and other vocal features beyond speech, based on vocal data from many different people, presenting the idea of a diverse and collective voice, initiating a reflection of the sonic appearance of future synthesized speech that goes beyond the binary.