First Attempt of Gender-free Speech Style Transfer for Genderless Robot

Abstract

Some robots for human-robot interaction are designed with female or male physical appearance. Other robots are endowed with no gender characteristics, namely genderless robots, such as Pepper and NAO robot. A robot with male or female physical appearance should possess the mapped speech gender style during a natural human-robot interaction, which can be learned from humans' male or female speech. In this paper, we make a new trial to synthesis gender-free speeches for physically genderless robots, which is promising in order to improve a more natural human-robot interaction with genderless robots. Our gender style-controlled speech synthesizer takes the speech text and gender style embedding as inputs to generate speech audio. A speech gender encoder network is used to extract the embedding of the speech gender style with female and male speeches as input. Based on the distribution of the female and male gender style embedding, we explore the gender-free speech style embedding space where we sample some gender-free embedding vectors to generate genderless speech audio. This is a preliminary work where we show how the genderless speech audio wave will be synthesized from text.