Perception of Paralinguistic Traits in Synthesized Voices

Abstract

Along with the rise of artificial intelligence and the internet-of-things, synthesized voices are now common in daily--life, providing us with guidance, assistance, and even companionship. From formant to concatenative synthesis, the synthesized voice continues to be defined by the same traits we prescribe to ourselves. When the recorded voice is synthesized, does our perception of its new machine embodiment change, and can we consider an alternative, more inclusive form? To begin evaluating the impact of aesthetic design, this study presents a first--step perception test to explore the paralinguistic traits of the synthesized voice. Using a corpus of 13 synthesized voices, constructed from acoustic concatenative speech synthesis, we assessed the response of 23 listeners from differing cultural backgrounds. To evaluate if perception shifts from the defined traits, we asked listeners to assigned traits of age, gender, accent origin, and human--likeness. Results present a difference in perception for age and human--likeness across voices, and a general agreement across listeners for both gender and accent origin. Connections found between age, gender and human--likeness call for further exploration into a more participatory and inclusive synthesized vocal identity.